---
_id: '13557'
abstract:
- lang: eng
text: We present a searchable encryption scheme for dynamic document collections
in a multi-user scenario. Our scheme features fine-grained access control to search
results, as well as access control to operations such as adding documents to the
document collection, or changing individual documents. The scheme features verifiability
of search results. Our scheme also satisfies the forward privacy notion crucial
for the security of dynamic searchable encryption schemes.
author:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
- first_name: Nils
full_name: Löken, Nils
id: '13703'
last_name: Löken
citation:
ama: 'Blömer J, Löken N. Dynamic Searchable Encryption with Access Control. In:
12th International Symposium on Foundations and Practice of Security, FPS 2019.
Vol 12056. LNCS. Springer; 2019.'
apa: Blömer, J., & Löken, N. (2019). Dynamic Searchable Encryption with Access
Control. In 12th International Symposium on Foundations and Practice of Security,
FPS 2019 (Vol. 12056). Springer.
bibtex: '@inproceedings{Blömer_Löken_2019, series={LNCS}, title={Dynamic Searchable
Encryption with Access Control}, volume={12056}, booktitle={12th International
Symposium on Foundations and Practice of Security, FPS 2019}, publisher={Springer},
author={Blömer, Johannes and Löken, Nils}, year={2019}, collection={LNCS} }'
chicago: Blömer, Johannes, and Nils Löken. “Dynamic Searchable Encryption with Access
Control.” In 12th International Symposium on Foundations and Practice of Security,
FPS 2019, Vol. 12056. LNCS. Springer, 2019.
ieee: J. Blömer and N. Löken, “Dynamic Searchable Encryption with Access Control,”
in 12th International Symposium on Foundations and Practice of Security, FPS
2019, 2019, vol. 12056.
mla: Blömer, Johannes, and Nils Löken. “Dynamic Searchable Encryption with Access
Control.” 12th International Symposium on Foundations and Practice of Security,
FPS 2019, vol. 12056, Springer, 2019.
short: 'J. Blömer, N. Löken, in: 12th International Symposium on Foundations and
Practice of Security, FPS 2019, Springer, 2019.'
date_created: 2019-10-01T08:05:31Z
date_updated: 2022-01-06T06:51:38Z
department:
- _id: '64'
- _id: '568'
intvolume: ' 12056'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://eprint.iacr.org/2019/1038
oa: '1'
publication: 12th International Symposium on Foundations and Practice of Security,
FPS 2019
publisher: Springer
series_title: LNCS
status: public
title: Dynamic Searchable Encryption with Access Control
type: conference
user_id: '13703'
volume: 12056
year: '2019'
...
---
_id: '13592'
author:
- first_name: Matthias
full_name: Pilot, Matthias
last_name: Pilot
citation:
ama: Pilot M. Efficient Finite-Field Arithmetic for Elliptic Curve Cryptography
in Java. Universität Paderborn; 2019.
apa: Pilot, M. (2019). Efficient Finite-Field Arithmetic for Elliptic Curve Cryptography
in Java. Universität Paderborn.
bibtex: '@book{Pilot_2019, title={Efficient Finite-Field Arithmetic for Elliptic
Curve Cryptography in Java}, publisher={Universität Paderborn}, author={Pilot,
Matthias}, year={2019} }'
chicago: Pilot, Matthias. Efficient Finite-Field Arithmetic for Elliptic Curve
Cryptography in Java. Universität Paderborn, 2019.
ieee: M. Pilot, Efficient Finite-Field Arithmetic for Elliptic Curve Cryptography
in Java. Universität Paderborn, 2019.
mla: Pilot, Matthias. Efficient Finite-Field Arithmetic for Elliptic Curve Cryptography
in Java. Universität Paderborn, 2019.
short: M. Pilot, Efficient Finite-Field Arithmetic for Elliptic Curve Cryptography
in Java, Universität Paderborn, 2019.
date_created: 2019-10-03T12:30:24Z
date_updated: 2022-01-06T06:51:40Z
department:
- _id: '7'
- _id: '64'
extern: '1'
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '13'
name: SFB 901 - Subproject C1
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
title: Efficient Finite-Field Arithmetic for Elliptic Curve Cryptography in Java
type: bachelorsthesis
user_id: '477'
year: '2019'
...
---
_id: '13648'
author:
- first_name: Swante
full_name: Scholz, Swante
last_name: Scholz
citation:
ama: Scholz S. Implementation and Comparison of Elliptic Curve Algorithms in
Java. Universität Paderborn; 2019.
apa: Scholz, S. (2019). Implementation and Comparison of Elliptic Curve Algorithms
in Java. Universität Paderborn.
bibtex: '@book{Scholz_2019, title={Implementation and Comparison of Elliptic Curve
Algorithms in Java}, publisher={Universität Paderborn}, author={Scholz, Swante},
year={2019} }'
chicago: Scholz, Swante. Implementation and Comparison of Elliptic Curve Algorithms
in Java. Universität Paderborn, 2019.
ieee: S. Scholz, Implementation and Comparison of Elliptic Curve Algorithms in
Java. Universität Paderborn, 2019.
mla: Scholz, Swante. Implementation and Comparison of Elliptic Curve Algorithms
in Java. Universität Paderborn, 2019.
short: S. Scholz, Implementation and Comparison of Elliptic Curve Algorithms in
Java, Universität Paderborn, 2019.
date_created: 2019-10-07T09:56:58Z
date_updated: 2022-01-06T06:51:41Z
ddc:
- '000'
department:
- _id: '7'
- _id: '64'
extern: '1'
file:
- access_level: open_access
content_type: application/pdf
creator: jbobolz
date_created: 2020-04-27T10:32:00Z
date_updated: 2020-04-27T10:33:59Z
file_id: '16871'
file_name: sscholz-MA-thesis-final.pdf
file_size: 1714805
relation: main_file
file_date_updated: 2020-04-27T10:33:59Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '13'
name: SFB 901 - Subproject C1
publisher: Universität Paderborn
status: public
supervisor:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
title: Implementation and Comparison of Elliptic Curve Algorithms in Java
type: mastersthesis
user_id: '477'
year: '2019'
...
---
_id: '13652'
author:
- first_name: Kristian
full_name: Hinnenthal, Kristian
id: '32229'
last_name: Hinnenthal
- first_name: Christian
full_name: Scheideler, Christian
id: '20792'
last_name: Scheideler
- first_name: Martijn
full_name: Struijs, Martijn
last_name: Struijs
citation:
ama: 'Hinnenthal K, Scheideler C, Struijs M. Fast Distributed Algorithms for LP-Type
Problems of Low Dimension. In: 33rd International Symposium on Distributed
Computing (DISC 2019). ; 2019. doi:10.4230/LIPICS.DISC.2019.23'
apa: Hinnenthal, K., Scheideler, C., & Struijs, M. (2019). Fast Distributed
Algorithms for LP-Type Problems of Low Dimension. In 33rd International Symposium
on Distributed Computing (DISC 2019). https://doi.org/10.4230/LIPICS.DISC.2019.23
bibtex: '@inproceedings{Hinnenthal_Scheideler_Struijs_2019, title={Fast Distributed
Algorithms for LP-Type Problems of Low Dimension}, DOI={10.4230/LIPICS.DISC.2019.23},
booktitle={33rd International Symposium on Distributed Computing (DISC 2019)},
author={Hinnenthal, Kristian and Scheideler, Christian and Struijs, Martijn},
year={2019} }'
chicago: Hinnenthal, Kristian, Christian Scheideler, and Martijn Struijs. “Fast
Distributed Algorithms for LP-Type Problems of Low Dimension.” In 33rd International
Symposium on Distributed Computing (DISC 2019), 2019. https://doi.org/10.4230/LIPICS.DISC.2019.23.
ieee: K. Hinnenthal, C. Scheideler, and M. Struijs, “Fast Distributed Algorithms
for LP-Type Problems of Low Dimension,” in 33rd International Symposium on
Distributed Computing (DISC 2019), 2019.
mla: Hinnenthal, Kristian, et al. “Fast Distributed Algorithms for LP-Type Problems
of Low Dimension.” 33rd International Symposium on Distributed Computing (DISC
2019), 2019, doi:10.4230/LIPICS.DISC.2019.23.
short: 'K. Hinnenthal, C. Scheideler, M. Struijs, in: 33rd International Symposium
on Distributed Computing (DISC 2019), 2019.'
date_created: 2019-10-08T11:53:38Z
date_updated: 2022-01-06T06:51:41Z
department:
- _id: '79'
doi: 10.4230/LIPICS.DISC.2019.23
language:
- iso: eng
project:
- _id: '1'
name: SFB 901
- _id: '2'
name: SFB 901 - Project Area A
- _id: '5'
name: SFB 901 - Subproject A1
publication: 33rd International Symposium on Distributed Computing (DISC 2019)
status: public
title: Fast Distributed Algorithms for LP-Type Problems of Low Dimension
type: conference
user_id: '32229'
year: '2019'
...
---
_id: '13679'
author:
- first_name: Sascha
full_name: Brauer, Sascha
id: '13291'
last_name: Brauer
citation:
ama: Brauer S. Classification and Approximation of Geometric Location Problems.
Paderborn; 2019. doi:10.17619/UNIPB/1-816
apa: Brauer, S. (2019). Classification and Approximation of Geometric Location
Problems. Paderborn. https://doi.org/10.17619/UNIPB/1-816
bibtex: '@book{Brauer_2019, place={Paderborn}, title={Classification and Approximation
of Geometric Location Problems}, DOI={10.17619/UNIPB/1-816},
author={Brauer, Sascha}, year={2019} }'
chicago: Brauer, Sascha. Classification and Approximation of Geometric Location
Problems. Paderborn, 2019. https://doi.org/10.17619/UNIPB/1-816.
ieee: S. Brauer, Classification and Approximation of Geometric Location Problems.
Paderborn, 2019.
mla: Brauer, Sascha. Classification and Approximation of Geometric Location Problems.
2019, doi:10.17619/UNIPB/1-816.
short: S. Brauer, Classification and Approximation of Geometric Location Problems,
Paderborn, 2019.
date_created: 2019-10-09T10:00:53Z
date_updated: 2022-01-06T06:51:41Z
department:
- _id: '64'
doi: 10.17619/UNIPB/1-816
language:
- iso: eng
place: Paderborn
project:
- _id: '45'
name: Soft-Clustering - Von Heuristiken zu Approximationsalgorithmen
status: public
supervisor:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
title: Classification and Approximation of Geometric Location Problems
type: dissertation
user_id: '13291'
year: '2019'
...
---
_id: '7626'
author:
- first_name: Philipp
full_name: Schubert, Philipp
id: '60543'
last_name: Schubert
orcid: 0000-0002-8674-1859
- first_name: Ben
full_name: Hermann, Ben
id: '66173'
last_name: Hermann
orcid: 0000-0001-9848-2017
- first_name: Eric
full_name: Bodden, Eric
id: '59256'
last_name: Bodden
orcid: 0000-0003-3470-3647
citation:
ama: 'Schubert P, Hermann B, Bodden E. PhASAR: An Inter-Procedural Static Analysis
Framework for C/C++. In: Proceedings of the 25th International Conference on
Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2019),
Held as Part of the European Joint Conferences on Theory and Practice of Software
(ETAPS 2019). Vol II. ; 2019:393-410. doi:10.1007/978-3-030-17465-1_22'
apa: 'Schubert, P., Hermann, B., & Bodden, E. (2019). PhASAR: An Inter-Procedural
Static Analysis Framework for C/C++. Proceedings of the 25th International
Conference on Tools and Algorithms for the Construction and Analysis of Systems
(TACAS 2019), Held as Part of the European Joint Conferences on Theory and Practice
of Software (ETAPS 2019), II, 393–410. https://doi.org/10.1007/978-3-030-17465-1_22'
bibtex: '@inproceedings{Schubert_Hermann_Bodden_2019, title={PhASAR: An Inter-Procedural
Static Analysis Framework for C/C++}, volume={II}, DOI={10.1007/978-3-030-17465-1_22},
booktitle={Proceedings of the 25th International Conference on Tools and Algorithms
for the Construction and Analysis of Systems (TACAS 2019), Held as Part of the
European Joint Conferences on Theory and Practice of Software (ETAPS 2019)}, author={Schubert,
Philipp and Hermann, Ben and Bodden, Eric}, year={2019}, pages={393–410} }'
chicago: 'Schubert, Philipp, Ben Hermann, and Eric Bodden. “PhASAR: An Inter-Procedural
Static Analysis Framework for C/C++.” In Proceedings of the 25th International
Conference on Tools and Algorithms for the Construction and Analysis of Systems
(TACAS 2019), Held as Part of the European Joint Conferences on Theory and Practice
of Software (ETAPS 2019), II:393–410, 2019. https://doi.org/10.1007/978-3-030-17465-1_22.'
ieee: 'P. Schubert, B. Hermann, and E. Bodden, “PhASAR: An Inter-Procedural Static
Analysis Framework for C/C++,” in Proceedings of the 25th International Conference
on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2019),
Held as Part of the European Joint Conferences on Theory and Practice of Software
(ETAPS 2019), Prague, Czech Republic, 2019, vol. II, pp. 393–410, doi: 10.1007/978-3-030-17465-1_22.'
mla: 'Schubert, Philipp, et al. “PhASAR: An Inter-Procedural Static Analysis Framework
for C/C++.” Proceedings of the 25th International Conference on Tools and Algorithms
for the Construction and Analysis of Systems (TACAS 2019), Held as Part of the
European Joint Conferences on Theory and Practice of Software (ETAPS 2019),
vol. II, 2019, pp. 393–410, doi:10.1007/978-3-030-17465-1_22.'
short: 'P. Schubert, B. Hermann, E. Bodden, in: Proceedings of the 25th International
Conference on Tools and Algorithms for the Construction and Analysis of Systems
(TACAS 2019), Held as Part of the European Joint Conferences on Theory and Practice
of Software (ETAPS 2019), 2019, pp. 393–410.'
conference:
end_date: 2019-04-11
location: Prague, Czech Republic
name: 25th International Conference on Tools and Algorithms for the Construction
and Analysis of Systems (TACAS)
start_date: 2019-04-08
date_created: 2019-02-12T07:20:07Z
date_updated: 2022-03-25T07:48:36Z
ddc:
- '000'
department:
- _id: '76'
doi: 10.1007/978-3-030-17465-1_22
file:
- access_level: closed
content_type: application/pdf
creator: pdschbrt
date_created: 2019-02-12T07:18:17Z
date_updated: 2019-02-12T07:18:17Z
file_id: '7627'
file_name: main.pdf
file_size: 504897
relation: main_file
success: 1
file_date_updated: 2019-02-12T07:18:17Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/chapter/10.1007/978-3-030-17465-1_22
oa: '1'
page: 393-410
project:
- _id: '1'
name: SFB 901
- _id: '12'
name: SFB 901 - Subproject B4
- _id: '3'
name: SFB 901 - Project Area B
publication: Proceedings of the 25th International Conference on Tools and Algorithms
for the Construction and Analysis of Systems (TACAS 2019), Held as Part of the European
Joint Conferences on Theory and Practice of Software (ETAPS 2019)
publication_status: published
status: public
title: 'PhASAR: An Inter-Procedural Static Analysis Framework for C/C++'
type: conference
user_id: '60543'
volume: II
year: '2019'
...
---
_id: '31067'
author:
- first_name: Zakarya
full_name: Guettatfi, Zakarya
last_name: Guettatfi
- first_name: Marco
full_name: Platzner, Marco
id: '398'
last_name: Platzner
- first_name: Omar
full_name: Kermia, Omar
last_name: Kermia
- first_name: Abdelhakim
full_name: Khouas, Abdelhakim
last_name: Khouas
citation:
ama: 'Guettatfi Z, Platzner M, Kermia O, Khouas A. An Approach for Mapping Periodic
Real-Time Tasks to Reconfigurable Hardware. In: 2019 IEEE International Parallel
and Distributed Processing Symposium Workshops (IPDPSW). IEEE; 2019. doi:10.1109/ipdpsw.2019.00027'
apa: Guettatfi, Z., Platzner, M., Kermia, O., & Khouas, A. (2019). An Approach
for Mapping Periodic Real-Time Tasks to Reconfigurable Hardware. 2019 IEEE
International Parallel and Distributed Processing Symposium Workshops (IPDPSW).
https://doi.org/10.1109/ipdpsw.2019.00027
bibtex: '@inproceedings{Guettatfi_Platzner_Kermia_Khouas_2019, title={An Approach
for Mapping Periodic Real-Time Tasks to Reconfigurable Hardware}, DOI={10.1109/ipdpsw.2019.00027},
booktitle={2019 IEEE International Parallel and Distributed Processing Symposium
Workshops (IPDPSW)}, publisher={IEEE}, author={Guettatfi, Zakarya and Platzner,
Marco and Kermia, Omar and Khouas, Abdelhakim}, year={2019} }'
chicago: Guettatfi, Zakarya, Marco Platzner, Omar Kermia, and Abdelhakim Khouas.
“An Approach for Mapping Periodic Real-Time Tasks to Reconfigurable Hardware.”
In 2019 IEEE International Parallel and Distributed Processing Symposium Workshops
(IPDPSW). IEEE, 2019. https://doi.org/10.1109/ipdpsw.2019.00027.
ieee: 'Z. Guettatfi, M. Platzner, O. Kermia, and A. Khouas, “An Approach for Mapping
Periodic Real-Time Tasks to Reconfigurable Hardware,” 2019, doi: 10.1109/ipdpsw.2019.00027.'
mla: Guettatfi, Zakarya, et al. “An Approach for Mapping Periodic Real-Time Tasks
to Reconfigurable Hardware.” 2019 IEEE International Parallel and Distributed
Processing Symposium Workshops (IPDPSW), IEEE, 2019, doi:10.1109/ipdpsw.2019.00027.
short: 'Z. Guettatfi, M. Platzner, O. Kermia, A. Khouas, in: 2019 IEEE International
Parallel and Distributed Processing Symposium Workshops (IPDPSW), IEEE, 2019.'
date_created: 2022-05-05T07:42:26Z
date_updated: 2022-05-05T07:43:29Z
department:
- _id: '78'
doi: 10.1109/ipdpsw.2019.00027
language:
- iso: eng
publication: 2019 IEEE International Parallel and Distributed Processing Symposium
Workshops (IPDPSW)
publication_status: published
publisher: IEEE
status: public
title: An Approach for Mapping Periodic Real-Time Tasks to Reconfigurable Hardware
type: conference
user_id: '398'
year: '2019'
...
---
_id: '15332'
abstract:
- lang: eng
text: "Artificial intelligence (AI) has the potential for far-reaching – in our
opinion – irreversible changes.\r\nThey range from effects on the individual and
society to new societal and social issues. The question arises\r\nas to how students
can learn the basic functioning of AI systems, what areas of life and society
are affected\r\nby these and – most important – how their own lives are affected
by these changes. Therefore, we are developing and evaluating school materials
for the German ”Science Year AI”. It can be used for students of all\r\nschool
types from the seventh grade upwards and will be distributed to about 2000 schools
in autumn with\r\nthe support of the Federal Ministry of Education and Research.
The material deals with the following aspects\r\nof AI: Discussing everyday experiences
with AI, how does machine learning work, historical development\r\nof AI concepts,
difference between man and machine, future distribution of roles between man and
machine,\r\nin which AI world do we want to live and how much AI would we like
to have in our lives. Through an\r\naccompanying evaluation, high quality of the
technical content and didactic preparation is achieved in order\r\nto guarantee
the long-term applicability in the teaching context in the different age groups
and school types.\r\nIn this paper, we describe the current state of the material
development, the challenges arising, and the results\r\nof tests with different
classes to date. We also present first ideas for evaluating the results."
author:
- first_name: Michael
full_name: Schlichtig, Michael
id: '32312'
last_name: Schlichtig
orcid: 0000-0001-6600-6171
- first_name: Simone Anna
full_name: Opel, Simone Anna
id: '72932'
last_name: Opel
- first_name: Lea
full_name: Budde, Lea
id: '32443'
last_name: Budde
- first_name: Carsten
full_name: Schulte, Carsten
id: '60311'
last_name: Schulte
citation:
ama: 'Schlichtig M, Opel SA, Budde L, Schulte C. Understanding Artificial Intelligence
– A Project for the Development of Comprehensive Teaching Material. In: Jasutė
E, Pozdniakov S, eds. ISSEP 2019 - 12th International Conference on Informatics
in Schools: Situation, Evaluation and Perspectives, Local Proceedings. Vol
12. ; 2019:65-73.'
apa: 'Schlichtig, M., Opel, S. A., Budde, L., & Schulte, C. (2019). Understanding
Artificial Intelligence – A Project for the Development of Comprehensive Teaching
Material. In E. Jasutė & S. Pozdniakov (Eds.), ISSEP 2019 - 12th International
conference on informatics in schools: Situation, evaluation and perspectives,
Local Proceedings (Vol. 12, pp. 65–73).'
bibtex: '@inproceedings{Schlichtig_Opel_Budde_Schulte_2019, title={Understanding
Artificial Intelligence – A Project for the Development of Comprehensive Teaching
Material}, volume={12}, booktitle={ISSEP 2019 - 12th International conference
on informatics in schools: Situation, evaluation and perspectives, Local Proceedings},
author={Schlichtig, Michael and Opel, Simone Anna and Budde, Lea and Schulte,
Carsten}, editor={Jasutė, Eglė and Pozdniakov, Sergei}, year={2019}, pages={65–73}
}'
chicago: 'Schlichtig, Michael, Simone Anna Opel, Lea Budde, and Carsten Schulte.
“Understanding Artificial Intelligence – A Project for the Development of Comprehensive
Teaching Material.” In ISSEP 2019 - 12th International Conference on Informatics
in Schools: Situation, Evaluation and Perspectives, Local Proceedings, edited
by Eglė Jasutė and Sergei Pozdniakov, 12:65–73, 2019.'
ieee: 'M. Schlichtig, S. A. Opel, L. Budde, and C. Schulte, “Understanding Artificial
Intelligence – A Project for the Development of Comprehensive Teaching Material,”
in ISSEP 2019 - 12th International conference on informatics in schools: Situation,
evaluation and perspectives, Local Proceedings, Lanarca, 2019, vol. 12, pp.
65–73.'
mla: 'Schlichtig, Michael, et al. “Understanding Artificial Intelligence – A Project
for the Development of Comprehensive Teaching Material.” ISSEP 2019 - 12th
International Conference on Informatics in Schools: Situation, Evaluation and
Perspectives, Local Proceedings, edited by Eglė Jasutė and Sergei Pozdniakov,
vol. 12, 2019, pp. 65–73.'
short: 'M. Schlichtig, S.A. Opel, L. Budde, C. Schulte, in: E. Jasutė, S. Pozdniakov
(Eds.), ISSEP 2019 - 12th International Conference on Informatics in Schools:
Situation, Evaluation and Perspectives, Local Proceedings, 2019, pp. 65–73.'
conference:
end_date: 2019-11-20
location: Lanarca
name: 'ISSEP 2019 - 12th International conference on informatics in schools: Situation,
evaluation and perspectives'
start_date: 2019-11-18
date_created: 2019-12-16T17:50:08Z
date_updated: 2022-07-26T11:41:41Z
department:
- _id: '67'
editor:
- first_name: Eglė
full_name: Jasutė, Eglė
last_name: Jasutė
- first_name: Sergei
full_name: Pozdniakov, Sergei
last_name: Pozdniakov
intvolume: ' 12'
keyword:
- Artificial Intelligence
- Machine Learning
- Teaching Material
- Societal Aspects
- Ethics. Social Aspects
- Science Year
- Simulation Game
language:
- iso: eng
main_file_link:
- url: http://cyprusconferences.org/issep2019/wp-content/uploads/2019/10/LocalISSEP-v5.pdf
page: 65 - 73
publication: 'ISSEP 2019 - 12th International conference on informatics in schools:
Situation, evaluation and perspectives, Local Proceedings'
publication_identifier:
isbn:
- 978-9925-553-27-3
publication_status: published
quality_controlled: '1'
status: public
title: Understanding Artificial Intelligence – A Project for the Development of Comprehensive
Teaching Material
type: conference
user_id: '32312'
volume: 12
year: '2019'
...
---
_id: '15643'
author:
- first_name: Simone Anna
full_name: Opel, Simone Anna
id: '72932'
last_name: Opel
- first_name: Michael
full_name: Schlichtig, Michael
id: '32312'
last_name: Schlichtig
orcid: 0000-0001-6600-6171
- first_name: Carsten
full_name: Schulte, Carsten
id: '60311'
last_name: Schulte
citation:
ama: 'Opel SA, Schlichtig M, Schulte C. Developing Teaching Materials on Artificial
Intelligence by Using a Simulation Game (Work in Progress). In: WiPSCE.
ACM; 2019:11:1-11:2.'
apa: Opel, S. A., Schlichtig, M., & Schulte, C. (2019). Developing Teaching
Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress).
WiPSCE, 11:1-11:2.
bibtex: '@inproceedings{Opel_Schlichtig_Schulte_2019, title={Developing Teaching
Materials on Artificial Intelligence by Using a Simulation Game (Work in Progress)},
booktitle={WiPSCE}, publisher={ACM}, author={Opel, Simone Anna and Schlichtig,
Michael and Schulte, Carsten}, year={2019}, pages={11:1-11:2} }'
chicago: Opel, Simone Anna, Michael Schlichtig, and Carsten Schulte. “Developing
Teaching Materials on Artificial Intelligence by Using a Simulation Game (Work
in Progress).” In WiPSCE, 11:1-11:2. ACM, 2019.
ieee: S. A. Opel, M. Schlichtig, and C. Schulte, “Developing Teaching Materials
on Artificial Intelligence by Using a Simulation Game (Work in Progress),” in
WiPSCE, 2019, p. 11:1-11:2.
mla: Opel, Simone Anna, et al. “Developing Teaching Materials on Artificial Intelligence
by Using a Simulation Game (Work in Progress).” WiPSCE, ACM, 2019, p. 11:1-11:2.
short: 'S.A. Opel, M. Schlichtig, C. Schulte, in: WiPSCE, ACM, 2019, p. 11:1-11:2.'
date_created: 2020-01-28T10:28:37Z
date_updated: 2022-07-26T11:41:51Z
department:
- _id: '67'
language:
- iso: eng
page: 11:1-11:2
publication: WiPSCE
publisher: ACM
quality_controlled: '1'
status: public
title: Developing Teaching Materials on Artificial Intelligence by Using a Simulation
Game (Work in Progress)
type: conference
user_id: '32312'
year: '2019'
...
---
_id: '13259'
author:
- first_name: Wei-Fan
full_name: Chen, Wei-Fan
id: '82920'
last_name: Chen
- first_name: Khalid
full_name: Al-Khatib, Khalid
last_name: Al-Khatib
- first_name: Matthias
full_name: Hagen, Matthias
last_name: Hagen
- first_name: Henning
full_name: Wachsmuth, Henning
id: '3900'
last_name: Wachsmuth
- first_name: Benno
full_name: Stein, Benno
last_name: Stein
citation:
ama: 'Chen W-F, Al-Khatib K, Hagen M, Wachsmuth H, Stein B. Unraveling the Search
Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition. In: Proceedings
of the Second Workshop on Natural Language Processing for Internet Freedom.
; 2019:76-82.'
apa: Chen, W.-F., Al-Khatib, K., Hagen, M., Wachsmuth, H., & Stein, B. (2019).
Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon
Acquisition. Proceedings of the Second Workshop on Natural Language Processing
for Internet Freedom, 76–82.
bibtex: '@inproceedings{Chen_Al-Khatib_Hagen_Wachsmuth_Stein_2019, title={Unraveling
the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition},
booktitle={Proceedings of the Second Workshop on Natural Language Processing for
Internet Freedom}, author={Chen, Wei-Fan and Al-Khatib, Khalid and Hagen, Matthias
and Wachsmuth, Henning and Stein, Benno}, year={2019}, pages={76–82} }'
chicago: Chen, Wei-Fan, Khalid Al-Khatib, Matthias Hagen, Henning Wachsmuth, and
Benno Stein. “Unraveling the Search Space of Abusive Language in Wikipedia with
Dynamic Lexicon Acquisition.” In Proceedings of the Second Workshop on Natural
Language Processing for Internet Freedom, 76–82, 2019.
ieee: W.-F. Chen, K. Al-Khatib, M. Hagen, H. Wachsmuth, and B. Stein, “Unraveling
the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition,”
in Proceedings of the Second Workshop on Natural Language Processing for Internet
Freedom, 2019, pp. 76–82.
mla: Chen, Wei-Fan, et al. “Unraveling the Search Space of Abusive Language in Wikipedia
with Dynamic Lexicon Acquisition.” Proceedings of the Second Workshop on Natural
Language Processing for Internet Freedom, 2019, pp. 76–82.
short: 'W.-F. Chen, K. Al-Khatib, M. Hagen, H. Wachsmuth, B. Stein, in: Proceedings
of the Second Workshop on Natural Language Processing for Internet Freedom, 2019,
pp. 76–82.'
date_created: 2019-09-17T14:42:43Z
date_updated: 2022-05-09T15:04:18Z
department:
- _id: '600'
- _id: '568'
language:
- iso: eng
main_file_link:
- url: https://www.aclweb.org/anthology/D19-5009.pdf
page: 76-82
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '9'
name: 'SFB 901 - B1: SFB 901 - Subproject B1'
publication: Proceedings of the Second Workshop on Natural Language Processing for
Internet Freedom
status: public
title: Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon
Acquisition
type: conference
user_id: '82920'
year: '2019'
...
---
_id: '13904'
abstract:
- lang: eng
text: In this paper, we introduce updatable anonymous credential systems (UACS)
and use them to construct a new privacy-preserving incentive system. In a UACS,
a user holding a credential certifying some attributes can interact with the corresponding
issuer to update his attributes. During this, the issuer knows which update function
is run, but does not learn the user's previous attributes. Hence the update process
preserves anonymity of the user. One example for a class of update functions are
additive updates of integer attributes, where the issuer increments an unknown
integer attribute value v by some known value k. This kind of update is motivated
by an application of UACS to incentive systems. Users in an incentive system can
anonymously accumulate points, e.g. in a shop at checkout, and spend them later,
e.g. for a discount.
author:
- first_name: Johannes
full_name: Blömer, Johannes
id: '23'
last_name: Blömer
- first_name: Jan
full_name: Bobolz, Jan
id: '27207'
last_name: Bobolz
- first_name: Denis Pascal
full_name: Diemert, Denis Pascal
id: '44071'
last_name: Diemert
- first_name: Fabian
full_name: Eidens, Fabian
id: '25078'
last_name: Eidens
citation:
ama: 'Blömer J, Bobolz J, Diemert DP, Eidens F. Updatable Anonymous Credentials
and Applications to Incentive Systems. In: Proceedings of the 2019 ACM SIGSAC
Conference on Computer and Communications Security - CCS ’19. Proceedings
of the 2019 ACM SIGSAC Conference on Computer and Communications Security - CCS
’19. ; 2019. doi:10.1145/3319535.3354223'
apa: Blömer, J., Bobolz, J., Diemert, D. P., & Eidens, F. (2019). Updatable
Anonymous Credentials and Applications to Incentive Systems. Proceedings of
the 2019 ACM SIGSAC Conference on Computer and Communications Security - CCS ’19.
26th ACM Conference on Computer and Communications Security, London. https://doi.org/10.1145/3319535.3354223
bibtex: '@inproceedings{Blömer_Bobolz_Diemert_Eidens_2019, series={Proceedings of
the 2019 ACM SIGSAC Conference on Computer and Communications Security - CCS ’19},
title={Updatable Anonymous Credentials and Applications to Incentive Systems},
DOI={10.1145/3319535.3354223},
booktitle={Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications
Security - CCS ’19}, author={Blömer, Johannes and Bobolz, Jan and Diemert, Denis
Pascal and Eidens, Fabian}, year={2019}, collection={Proceedings of the 2019 ACM
SIGSAC Conference on Computer and Communications Security - CCS ’19} }'
chicago: Blömer, Johannes, Jan Bobolz, Denis Pascal Diemert, and Fabian Eidens.
“Updatable Anonymous Credentials and Applications to Incentive Systems.” In Proceedings
of the 2019 ACM SIGSAC Conference on Computer and Communications Security - CCS
’19. Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications
Security - CCS ’19, 2019. https://doi.org/10.1145/3319535.3354223.
ieee: 'J. Blömer, J. Bobolz, D. P. Diemert, and F. Eidens, “Updatable Anonymous
Credentials and Applications to Incentive Systems,” presented at the 26th ACM
Conference on Computer and Communications Security, London, 2019, doi: 10.1145/3319535.3354223.'
mla: Blömer, Johannes, et al. “Updatable Anonymous Credentials and Applications
to Incentive Systems.” Proceedings of the 2019 ACM SIGSAC Conference on Computer
and Communications Security - CCS ’19, 2019, doi:10.1145/3319535.3354223.
short: 'J. Blömer, J. Bobolz, D.P. Diemert, F. Eidens, in: Proceedings of the 2019
ACM SIGSAC Conference on Computer and Communications Security - CCS ’19, 2019.'
conference:
end_date: 2019-11-15
location: London
name: 26th ACM Conference on Computer and Communications Security
start_date: 2019-11-11
date_created: 2019-10-18T08:09:44Z
date_updated: 2023-01-10T10:25:27Z
ddc:
- '006'
department:
- _id: '7'
- _id: '64'
doi: 10.1145/3319535.3354223
file:
- access_level: closed
content_type: application/pdf
creator: jbobolz
date_created: 2019-10-18T08:07:49Z
date_updated: 2019-10-18T08:07:49Z
file_id: '13907'
file_name: full_eprinted_v2.pdf
file_size: 838949
relation: main_file
file_date_updated: 2019-10-18T08:07:49Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2019/169.pdf
oa: '1'
project:
- _id: '1'
name: SFB 901
- _id: '4'
name: SFB 901 - Project Area C
- _id: '13'
name: SFB 901 - Subproject C1
publication: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications
Security - CCS '19
series_title: Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications
Security - CCS '19
status: public
title: Updatable Anonymous Credentials and Applications to Incentive Systems
type: conference
user_id: '25078'
year: '2019'
...
---
_id: '46343'
abstract:
- lang: eng
text: This paper addresses multimodality of multi-objective (MO) optimization landscapes.
Contrary to common perception of local optima, according to which they are hindering
the progress of optimization algorithms, it will be shown that local efficient
sets in a multi-objective setting can assist optimizers in finding global efficient
sets. We use sophisticated visualization techniques, which rely on gradient field
heatmaps, to highlight those insights into landscape characteristics. Finally,
the MO local optimizer MOGSA is introduced, which exploits those observations
by sliding down the multi-objective gradient hill and moving along the local efficient
sets.
author:
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Grimme C, Kerschke P, Trautmann H. Multimodality in Multi-Objective Optimization
— More Boon than Bane? In: Deb K, Goodman E, Coello CCA, et al., eds. Proceedings
of the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization
(EMO). Vol 11411. Lecture Notes in Computer Science. Springer; 2019:126–138.
doi:10.1007/978-3-030-12598-1_11'
apa: Grimme, C., Kerschke, P., & Trautmann, H. (2019). Multimodality in Multi-Objective
Optimization — More Boon than Bane? In K. Deb, E. Goodman, C. C. A. Coello, K.
Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Proceedings of
the 10$^th$ International Conference on Evolutionary Multi-Criterion Optimization
(EMO) (Vol. 11411, pp. 126–138). Springer. https://doi.org/10.1007/978-3-030-12598-1_11
bibtex: '@inproceedings{Grimme_Kerschke_Trautmann_2019, place={East Lansing, MI,
USA}, series={Lecture Notes in Computer Science}, title={Multimodality in Multi-Objective
Optimization — More Boon than Bane?}, volume={11411}, DOI={10.1007/978-3-030-12598-1_11},
booktitle={Proceedings of the 10$^th$ International Conference on Evolutionary
Multi-Criterion Optimization (EMO)}, publisher={Springer}, author={Grimme, Christian
and Kerschke, Pascal and Trautmann, Heike}, editor={Deb, Kalyanmoy and Goodman,
Erik and Coello, Coello Carlos A. and Klamroth, Kathrin and Miettinen, Kaisa and
Mostaghim, Sanaz and Reed, Patrick}, year={2019}, pages={126–138}, collection={Lecture
Notes in Computer Science} }'
chicago: 'Grimme, Christian, Pascal Kerschke, and Heike Trautmann. “Multimodality
in Multi-Objective Optimization — More Boon than Bane?” In Proceedings of the
10$^th$ International Conference on Evolutionary Multi-Criterion Optimization
(EMO), edited by Kalyanmoy Deb, Erik Goodman, Coello Carlos A. Coello, Kathrin
Klamroth, Kaisa Miettinen, Sanaz Mostaghim, and Patrick Reed, 11411:126–138. Lecture
Notes in Computer Science. East Lansing, MI, USA: Springer, 2019. https://doi.org/10.1007/978-3-030-12598-1_11.'
ieee: 'C. Grimme, P. Kerschke, and H. Trautmann, “Multimodality in Multi-Objective
Optimization — More Boon than Bane?,” in Proceedings of the 10$^th$ International
Conference on Evolutionary Multi-Criterion Optimization (EMO), 2019, vol.
11411, pp. 126–138, doi: 10.1007/978-3-030-12598-1_11.'
mla: Grimme, Christian, et al. “Multimodality in Multi-Objective Optimization —
More Boon than Bane?” Proceedings of the 10$^th$ International Conference on
Evolutionary Multi-Criterion Optimization (EMO), edited by Kalyanmoy Deb et
al., vol. 11411, Springer, 2019, pp. 126–138, doi:10.1007/978-3-030-12598-1_11.
short: 'C. Grimme, P. Kerschke, H. Trautmann, in: K. Deb, E. Goodman, C.C.A. Coello,
K. Klamroth, K. Miettinen, S. Mostaghim, P. Reed (Eds.), Proceedings of the 10$^th$
International Conference on Evolutionary Multi-Criterion Optimization (EMO), Springer,
East Lansing, MI, USA, 2019, pp. 126–138.'
date_created: 2023-08-04T07:49:08Z
date_updated: 2023-10-16T13:31:03Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-030-12598-1_11
editor:
- first_name: Kalyanmoy
full_name: Deb, Kalyanmoy
last_name: Deb
- first_name: Erik
full_name: Goodman, Erik
last_name: Goodman
- first_name: Coello Carlos A.
full_name: Coello, Coello Carlos A.
last_name: Coello
- first_name: Kathrin
full_name: Klamroth, Kathrin
last_name: Klamroth
- first_name: Kaisa
full_name: Miettinen, Kaisa
last_name: Miettinen
- first_name: Sanaz
full_name: Mostaghim, Sanaz
last_name: Mostaghim
- first_name: Patrick
full_name: Reed, Patrick
last_name: Reed
intvolume: ' 11411'
language:
- iso: eng
page: 126–138
place: East Lansing, MI, USA
publication: Proceedings of the 10$^th$ International Conference on Evolutionary Multi-Criterion
Optimization (EMO)
publisher: Springer
series_title: Lecture Notes in Computer Science
status: public
title: Multimodality in Multi-Objective Optimization — More Boon than Bane?
type: conference
user_id: '15504'
volume: 11411
year: '2019'
...
---
_id: '46345'
abstract:
- lang: eng
text: It has long been observed that for practically any computational problem that
has been intensely studied, different instances are best solved using different
algorithms. This is particularly pronounced for computationally hard problems,
where in most cases, no single algorithm defines the state of the art; instead,
there is a set of algorithms with complementary strengths. This performance complementarity
can be exploited in various ways, one of which is based on the idea of selecting,
from a set of given algorithms, for each problem instance to be solved the one
expected to perform best. The task of automatically selecting an algorithm from
a given set is known as the per-instance algorithm selection problem and has been
intensely studied over the past 15 years, leading to major improvements in the
state of the art in solving a growing number of discrete combinatorial problems,
including propositional satisfiability and AI planning. Per-instance algorithm
selection also shows much promise for boosting performance in solving continuous
and mixed discrete/continuous optimisation problems. This survey provides an overview
of research in automated algorithm selection, ranging from early and seminal works
to recent and promising application areas. Different from earlier work, it covers
applications to discrete and continuous problems, and discusses algorithm selection
in context with conceptually related approaches, such as algorithm configuration,
scheduling, or portfolio selection. Since informative and cheaply computable problem
instance features provide the basis for effective per-instance algorithm selection
systems, we also provide an overview of such features for discrete and continuous
problems. Finally, we provide perspectives on future work in the area and discuss
a number of open research challenges.
author:
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Holger H
full_name: Hoos, Holger H
last_name: Hoos
- first_name: Frank
full_name: Neumann, Frank
last_name: Neumann
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Kerschke P, Hoos HH, Neumann F, Trautmann H. Automated Algorithm Selection:
Survey and Perspectives. Evolutionary Computation (ECJ). 2019;27(1):3–45.
doi:10.1162/evco_a_00242'
apa: 'Kerschke, P., Hoos, H. H., Neumann, F., & Trautmann, H. (2019). Automated
Algorithm Selection: Survey and Perspectives. Evolutionary Computation (ECJ),
27(1), 3–45. https://doi.org/10.1162/evco_a_00242'
bibtex: '@article{Kerschke_Hoos_Neumann_Trautmann_2019, title={Automated Algorithm
Selection: Survey and Perspectives}, volume={27}, DOI={10.1162/evco_a_00242},
number={1}, journal={Evolutionary Computation (ECJ)}, author={Kerschke, Pascal
and Hoos, Holger H and Neumann, Frank and Trautmann, Heike}, year={2019}, pages={3–45}
}'
chicago: 'Kerschke, Pascal, Holger H Hoos, Frank Neumann, and Heike Trautmann. “Automated
Algorithm Selection: Survey and Perspectives.” Evolutionary Computation (ECJ)
27, no. 1 (2019): 3–45. https://doi.org/10.1162/evco_a_00242.'
ieee: 'P. Kerschke, H. H. Hoos, F. Neumann, and H. Trautmann, “Automated Algorithm
Selection: Survey and Perspectives,” Evolutionary Computation (ECJ), vol.
27, no. 1, pp. 3–45, 2019, doi: 10.1162/evco_a_00242.'
mla: 'Kerschke, Pascal, et al. “Automated Algorithm Selection: Survey and Perspectives.”
Evolutionary Computation (ECJ), vol. 27, no. 1, 2019, pp. 3–45, doi:10.1162/evco_a_00242.'
short: P. Kerschke, H.H. Hoos, F. Neumann, H. Trautmann, Evolutionary Computation
(ECJ) 27 (2019) 3–45.
date_created: 2023-08-04T07:50:33Z
date_updated: 2023-10-16T13:31:40Z
department:
- _id: '34'
- _id: '819'
doi: 10.1162/evco_a_00242
intvolume: ' 27'
issue: '1'
language:
- iso: eng
page: 3–45
publication: Evolutionary Computation (ECJ)
status: public
title: 'Automated Algorithm Selection: Survey and Perspectives'
type: journal_article
user_id: '15504'
volume: 27
year: '2019'
...
---
_id: '46344'
abstract:
- lang: eng
text: Analyzing data streams has received considerable attention over the past decades
due to the widespread usage of sensors, social media and other streaming data
sources. A core research area in this field is stream clustering which aims to
recognize patterns in an unordered, infinite and evolving stream of observations.
Clustering can be a crucial support in decision making, since it aims for an optimized
aggregated representation of a continuous data stream over time and allows to
identify patterns in large and high-dimensional data. A multitude of algorithms
and approaches has been developed that are able to find and maintain clusters
over time in the challenging streaming scenario. This survey explores, summarizes
and categorizes a total of 51 stream clustering algorithms and identifies core
research threads over the past decades. In particular, it identifies categories
of algorithms based on distance thresholds, density grids and statistical models
as well as algorithms for high dimensional data. Furthermore, it discusses applications
scenarios, available software and how to configure stream clustering algorithms.
This survey is considerably more extensive than comparable studies, more up-to-date
and highlights how concepts are interrelated and have been developed over time.
author:
- first_name: Matthias
full_name: Carnein, Matthias
last_name: Carnein
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Carnein M, Trautmann H. Optimizing Data Stream Representation: An Extensive
Survey on Stream Clustering Algorithms. Business and Information Systems Engineering
(BISE). 2019;61(3):277–297.'
apa: 'Carnein, M., & Trautmann, H. (2019). Optimizing Data Stream Representation:
An Extensive Survey on Stream Clustering Algorithms. Business and Information
Systems Engineering (BISE), 61(3), 277–297.'
bibtex: '@article{Carnein_Trautmann_2019, title={Optimizing Data Stream Representation:
An Extensive Survey on Stream Clustering Algorithms}, volume={61}, number={3},
journal={Business and Information Systems Engineering (BISE)}, author={Carnein,
Matthias and Trautmann, Heike}, year={2019}, pages={277–297} }'
chicago: 'Carnein, Matthias, and Heike Trautmann. “Optimizing Data Stream Representation:
An Extensive Survey on Stream Clustering Algorithms.” Business and Information
Systems Engineering (BISE) 61, no. 3 (2019): 277–297.'
ieee: 'M. Carnein and H. Trautmann, “Optimizing Data Stream Representation: An Extensive
Survey on Stream Clustering Algorithms,” Business and Information Systems Engineering
(BISE), vol. 61, no. 3, pp. 277–297, 2019.'
mla: 'Carnein, Matthias, and Heike Trautmann. “Optimizing Data Stream Representation:
An Extensive Survey on Stream Clustering Algorithms.” Business and Information
Systems Engineering (BISE), vol. 61, no. 3, 2019, pp. 277–297.'
short: M. Carnein, H. Trautmann, Business and Information Systems Engineering (BISE)
61 (2019) 277–297.
date_created: 2023-08-04T07:49:47Z
date_updated: 2023-10-16T13:31:21Z
department:
- _id: '34'
- _id: '819'
intvolume: ' 61'
issue: '3'
language:
- iso: eng
page: 277–297
publication: Business and Information Systems Engineering (BISE)
status: public
title: 'Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering
Algorithms'
type: journal_article
user_id: '15504'
volume: 61
year: '2019'
...
---
_id: '46340'
abstract:
- lang: eng
text: Recommender systems aim to provide personalized suggestions to customers which
products to buy or services to consume. They can help to increase sales by helping
customers discover new and relevant products. Traditionally, recommender systems
use the purchase history of a customer, e.g., the purchased quantity or properties
of the items. While this allows to build personalized recommendations, it is a
very limited view of the problem. Nowadays, extensive information about customers
and their personal preferences is available which goes far beyond their purchase
behaviour. For example, customers reveal their preferences in social media, by
their browsing habits and online search behaviour or their interest in specific
newsletters. In this paper, we investigate how information from different sources
and channels can be collected and incorporated into the recommendation process.
We demonstrate this, based on a real-life case study of a retailer with several
million transactions. We discuss how to employ a recommender system in this scenario,
evaluate various recommendation strategies and describe how to incorporate information
from different sources and channels, both internal and external. Our results show
that the recommendations can be better tailored to the personal preferences of
customers.
author:
- first_name: Matthias
full_name: Carnein, Matthias
last_name: Carnein
- first_name: Leschek
full_name: Homann, Leschek
last_name: Homann
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
- first_name: Gottfried
full_name: Vossen, Gottfried
last_name: Vossen
citation:
ama: 'Carnein M, Homann L, Trautmann H, Vossen G. A Recommender System Based on
Omni-Channel Customer Data. In: Proceedings of the 21$^st$ IEEE Conference
on Business Informatics (CBI’ 19). ; 2019:65–74.'
apa: Carnein, M., Homann, L., Trautmann, H., & Vossen, G. (2019). A Recommender
System Based on Omni-Channel Customer Data. Proceedings of the 21$^st$ IEEE
Conference on Business Informatics (CBI’ 19), 65–74.
bibtex: '@inproceedings{Carnein_Homann_Trautmann_Vossen_2019, place={Moscow, Russia},
title={A Recommender System Based on Omni-Channel Customer Data}, booktitle={Proceedings
of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19)}, author={Carnein,
Matthias and Homann, Leschek and Trautmann, Heike and Vossen, Gottfried}, year={2019},
pages={65–74} }'
chicago: Carnein, Matthias, Leschek Homann, Heike Trautmann, and Gottfried Vossen.
“A Recommender System Based on Omni-Channel Customer Data.” In Proceedings
of the 21$^st$ IEEE Conference on Business Informatics (CBI’ 19), 65–74. Moscow,
Russia, 2019.
ieee: M. Carnein, L. Homann, H. Trautmann, and G. Vossen, “A Recommender System
Based on Omni-Channel Customer Data,” in Proceedings of the 21$^st$ IEEE Conference
on Business Informatics (CBI’ 19), 2019, pp. 65–74.
mla: Carnein, Matthias, et al. “A Recommender System Based on Omni-Channel Customer
Data.” Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’
19), 2019, pp. 65–74.
short: 'M. Carnein, L. Homann, H. Trautmann, G. Vossen, in: Proceedings of the 21$^st$
IEEE Conference on Business Informatics (CBI’ 19), Moscow, Russia, 2019, pp. 65–74.'
date_created: 2023-08-04T07:46:20Z
date_updated: 2023-10-16T13:29:53Z
department:
- _id: '34'
- _id: '819'
language:
- iso: eng
page: 65–74
place: Moscow, Russia
publication: Proceedings of the 21$^st$ IEEE Conference on Business Informatics (CBI’
19)
status: public
title: A Recommender System Based on Omni-Channel Customer Data
type: conference
user_id: '15504'
year: '2019'
...
---
_id: '46341'
abstract:
- lang: eng
text: Customer Segmentation aims to identify groups of customers that share similar
interest or behaviour. It is an essential tool in marketing and can be used to
target customer segments with tailored marketing strategies. Customer segmentation
is often based on clustering techniques. This analysis is typically performed
as a snapshot analysis where segments are identified at a specific point in time.
However, this ignores the fact that customer segments are highly volatile and
segments change over time. Once segments change, the entire analysis needs to
be repeated and strategies adapted. In this paper we explore stream clustering
as a tool to alleviate this problem. We propose a new stream clustering algorithm
which allows to identify and track customer segments over time. The biggest challenge
is that customer segmentation often relies on the transaction history of a customer.
Since this data changes over time, it is necessary to update customers which have
already been incorporated into the clustering. We show how to perform this step
incrementally, without the need for periodic re-computations. As a result, customer
segmentation can be performed continuously, faster and is more scalable. We demonstrate
the performance of our algorithm using a large real-life case study.
author:
- first_name: Matthias
full_name: Carnein, Matthias
last_name: Carnein
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Carnein M, Trautmann H. Customer Segmentation Based on Transactional Data
Using Stream Clustering. In: Proceedings of the 23$^rd$ Pacific-Asia Conference
on Knowledge Discovery and Data Mining (PAKDD ’19). ; 2019:280–292.'
apa: Carnein, M., & Trautmann, H. (2019). Customer Segmentation Based on Transactional
Data Using Stream Clustering. Proceedings of the 23$^rd$ Pacific-Asia Conference
on Knowledge Discovery and Data Mining (PAKDD ’19), 280–292.
bibtex: '@inproceedings{Carnein_Trautmann_2019, place={Macau, China}, title={Customer
Segmentation Based on Transactional Data Using Stream Clustering}, booktitle={Proceedings
of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery and Data Mining
(PAKDD ’19)}, author={Carnein, Matthias and Trautmann, Heike}, year={2019}, pages={280–292}
}'
chicago: Carnein, Matthias, and Heike Trautmann. “Customer Segmentation Based on
Transactional Data Using Stream Clustering.” In Proceedings of the 23$^rd$
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19),
280–292. Macau, China, 2019.
ieee: M. Carnein and H. Trautmann, “Customer Segmentation Based on Transactional
Data Using Stream Clustering,” in Proceedings of the 23$^rd$ Pacific-Asia Conference
on Knowledge Discovery and Data Mining (PAKDD ’19), 2019, pp. 280–292.
mla: Carnein, Matthias, and Heike Trautmann. “Customer Segmentation Based on Transactional
Data Using Stream Clustering.” Proceedings of the 23$^rd$ Pacific-Asia Conference
on Knowledge Discovery and Data Mining (PAKDD ’19), 2019, pp. 280–292.
short: 'M. Carnein, H. Trautmann, in: Proceedings of the 23$^rd$ Pacific-Asia Conference
on Knowledge Discovery and Data Mining (PAKDD ’19), Macau, China, 2019, pp. 280–292.'
date_created: 2023-08-04T07:47:20Z
date_updated: 2023-10-16T13:30:10Z
department:
- _id: '34'
- _id: '819'
language:
- iso: eng
page: 280–292
place: Macau, China
publication: Proceedings of the 23$^rd$ Pacific-Asia Conference on Knowledge Discovery
and Data Mining (PAKDD ’19)
status: public
title: Customer Segmentation Based on Transactional Data Using Stream Clustering
type: conference
user_id: '15504'
year: '2019'
...
---
_id: '46342'
abstract:
- lang: eng
text: There is a range of phenomena in continuous, global multi-objective optimization,
that cannot occur in single-objective optimization. For instance, in some multi-objective
optimization problems it is possible to follow continuous paths of gradients of
straightforward weighted scalarization functions, starting from locally efficient
solutions, in order to reach globally Pareto optimal solutions. This paper seeks
to better characterize multimodal multi-objective landscapes and to better understand
the transitions from local optima to global optima in simple, path-oriented search
procedures.
author:
- first_name: Christian
full_name: Grimme, Christian
last_name: Grimme
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Michael T M
full_name: Emmerich, Michael T M
last_name: Emmerich
- first_name: Mike
full_name: Preuss, Mike
last_name: Preuss
- first_name: André H
full_name: Deutz, André H
last_name: Deutz
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Grimme C, Kerschke P, Emmerich MTM, Preuss M, Deutz AH, Trautmann H. Sliding
to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal Multi-Objective
Optimization. In: AIP Conference Proceedings. AIP Publishing; 2019:020052-1-020052-020054.
doi:10.1063/1.5090019'
apa: 'Grimme, C., Kerschke, P., Emmerich, M. T. M., Preuss, M., Deutz, A. H., &
Trautmann, H. (2019). Sliding to the Global Optimum: How to Benefit from Non-Global
Optima in Multimodal Multi-Objective Optimization. AIP Conference Proceedings,
020052-1-020052–020054. https://doi.org/10.1063/1.5090019'
bibtex: '@inproceedings{Grimme_Kerschke_Emmerich_Preuss_Deutz_Trautmann_2019, place={Leiden,
The Netherlands}, title={Sliding to the Global Optimum: How to Benefit from Non-Global
Optima in Multimodal Multi-Objective Optimization}, DOI={10.1063/1.5090019},
booktitle={AIP Conference Proceedings}, publisher={AIP Publishing}, author={Grimme,
Christian and Kerschke, Pascal and Emmerich, Michael T M and Preuss, Mike and
Deutz, André H and Trautmann, Heike}, year={2019}, pages={020052-1-020052–4} }'
chicago: 'Grimme, Christian, Pascal Kerschke, Michael T M Emmerich, Mike Preuss,
André H Deutz, and Heike Trautmann. “Sliding to the Global Optimum: How to Benefit
from Non-Global Optima in Multimodal Multi-Objective Optimization.” In AIP
Conference Proceedings, 020052-1-020052–54. Leiden, The Netherlands: AIP Publishing,
2019. https://doi.org/10.1063/1.5090019.'
ieee: 'C. Grimme, P. Kerschke, M. T. M. Emmerich, M. Preuss, A. H. Deutz, and H.
Trautmann, “Sliding to the Global Optimum: How to Benefit from Non-Global Optima
in Multimodal Multi-Objective Optimization,” in AIP Conference Proceedings,
2019, pp. 020052-1-020052–4, doi: 10.1063/1.5090019.'
mla: 'Grimme, Christian, et al. “Sliding to the Global Optimum: How to Benefit from
Non-Global Optima in Multimodal Multi-Objective Optimization.” AIP Conference
Proceedings, AIP Publishing, 2019, pp. 020052-1-020052–54, doi:10.1063/1.5090019.'
short: 'C. Grimme, P. Kerschke, M.T.M. Emmerich, M. Preuss, A.H. Deutz, H. Trautmann,
in: AIP Conference Proceedings, AIP Publishing, Leiden, The Netherlands, 2019,
pp. 020052-1-020052–4.'
date_created: 2023-08-04T07:48:15Z
date_updated: 2023-10-16T13:30:43Z
department:
- _id: '34'
- _id: '819'
doi: 10.1063/1.5090019
language:
- iso: eng
page: 020052-1-020052-4
place: Leiden, The Netherlands
publication: AIP Conference Proceedings
publisher: AIP Publishing
status: public
title: 'Sliding to the Global Optimum: How to Benefit from Non-Global Optima in Multimodal
Multi-Objective Optimization'
type: conference
user_id: '15504'
year: '2019'
...
---
_id: '46336'
abstract:
- lang: eng
text: Choosing the best-performing optimizer(s) out of a portfolio of optimization
algorithms is usually a difficult and complex task. It gets even worse, if the
underlying functions are unknown, i.e., so-called black-box problems, and function
evaluations are considered to be expensive. In case of continuous single-objective
optimization problems, exploratory landscape analysis (ELA), a sophisticated and
effective approach for characterizing the landscapes of such problems by means
of numerical values before actually performing the optimization task itself, is
advantageous. Unfortunately, until now it has been quite complicated to compute
multiple ELA features simultaneously, as the corresponding code has been—if at
all—spread across multiple platforms or at least across several packages within
these platforms. This article presents a broad summary of existing ELA approaches
and introduces flacco, an R-package for feature-based landscape analysis of continuous
and constrained optimization problems. Although its functions neither solve the
optimization problem itself nor the related algorithm selection problem (ASP),
it offers easy access to an essential ingredient of the ASP by providing a wide
collection of ELA features on a single platform—even within a single package.
In addition, flacco provides multiple visualization techniques, which enhance
the understanding of some of these numerical features, and thereby make certain
landscape properties more comprehensible. On top of that, we will introduce the
package’s built-in, as well as web-hosted and hence platform-independent, graphical
user interface (GUI). It facilitates the usage of the package—especially for people
who are not familiar with R—and thus makes flacco a very convenient toolbox when
working towards algorithm selection of continuous single-objective optimization
problems.
author:
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Kerschke P, Trautmann H. Comprehensive Feature-Based Landscape Analysis of
Continuous and Constrained Optimization Problems Using the R-package flacco. In:
Bauer N, Ickstadt K, Lübke K, Szepannek G, Trautmann H, Vichi M, eds. Applications
in Statistical Computing. Springer; 2019:93–123. doi:10.1007/978-3-030-25147-5_7'
apa: Kerschke, P., & Trautmann, H. (2019). Comprehensive Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems Using the R-package
flacco. In N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, &
M. Vichi (Eds.), Applications in Statistical Computing (pp. 93–123). Springer.
https://doi.org/10.1007/978-3-030-25147-5_7
bibtex: '@inbook{Kerschke_Trautmann_2019, title={Comprehensive Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems Using the R-package
flacco}, DOI={10.1007/978-3-030-25147-5_7},
booktitle={Applications in Statistical Computing}, publisher={Springer}, author={Kerschke,
Pascal and Trautmann, Heike}, editor={Bauer, Nadja and Ickstadt, Katja and Lübke,
Karsten and Szepannek, Gero and Trautmann, Heike and Vichi, Maurizio}, year={2019},
pages={93–123} }'
chicago: Kerschke, Pascal, and Heike Trautmann. “Comprehensive Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems Using the R-Package
Flacco.” In Applications in Statistical Computing, edited by Nadja Bauer,
Katja Ickstadt, Karsten Lübke, Gero Szepannek, Heike Trautmann, and Maurizio Vichi,
93–123. Springer, 2019. https://doi.org/10.1007/978-3-030-25147-5_7.
ieee: P. Kerschke and H. Trautmann, “Comprehensive Feature-Based Landscape Analysis
of Continuous and Constrained Optimization Problems Using the R-package flacco,”
in Applications in Statistical Computing, N. Bauer, K. Ickstadt, K. Lübke,
G. Szepannek, H. Trautmann, and M. Vichi, Eds. Springer, 2019, pp. 93–123.
mla: Kerschke, Pascal, and Heike Trautmann. “Comprehensive Feature-Based Landscape
Analysis of Continuous and Constrained Optimization Problems Using the R-Package
Flacco.” Applications in Statistical Computing, edited by Nadja Bauer et
al., Springer, 2019, pp. 93–123, doi:10.1007/978-3-030-25147-5_7.
short: 'P. Kerschke, H. Trautmann, in: N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek,
H. Trautmann, M. Vichi (Eds.), Applications in Statistical Computing, Springer,
2019, pp. 93–123.'
date_created: 2023-08-04T07:43:30Z
date_updated: 2023-10-16T13:08:22Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-030-25147-5_7
editor:
- first_name: Nadja
full_name: Bauer, Nadja
last_name: Bauer
- first_name: Katja
full_name: Ickstadt, Katja
last_name: Ickstadt
- first_name: Karsten
full_name: Lübke, Karsten
last_name: Lübke
- first_name: Gero
full_name: Szepannek, Gero
last_name: Szepannek
- first_name: Heike
full_name: Trautmann, Heike
last_name: Trautmann
- first_name: Maurizio
full_name: Vichi, Maurizio
last_name: Vichi
language:
- iso: eng
page: 93–123
publication: Applications in Statistical Computing
publisher: Springer
status: public
title: Comprehensive Feature-Based Landscape Analysis of Continuous and Constrained
Optimization Problems Using the R-package flacco
type: book_chapter
user_id: '15504'
year: '2019'
...
---
_id: '46335'
author:
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: Trautmann H. Applications in Statistical Computing — From Music Data Analysis
to Industrial Quality Improvement. Springer International Publishing; 2019.
apa: Trautmann, H. (2019). Applications in Statistical Computing — From Music
Data Analysis to Industrial Quality Improvement. Springer International Publishing.
bibtex: '@book{Trautmann_2019, series={Studies in Classification, Data Analysis,
and Knowledge Organization}, title={Applications in Statistical Computing — From
Music Data Analysis to Industrial Quality Improvement}, publisher={Springer International
Publishing}, author={Trautmann, Heike}, year={2019}, collection={Studies in Classification,
Data Analysis, and Knowledge Organization} }'
chicago: Trautmann, Heike. Applications in Statistical Computing — From Music
Data Analysis to Industrial Quality Improvement. Studies in Classification,
Data Analysis, and Knowledge Organization. Springer International Publishing,
2019.
ieee: H. Trautmann, Applications in Statistical Computing — From Music Data Analysis
to Industrial Quality Improvement. Springer International Publishing, 2019.
mla: Trautmann, Heike. Applications in Statistical Computing — From Music Data
Analysis to Industrial Quality Improvement. Springer International Publishing,
2019.
short: H. Trautmann, Applications in Statistical Computing — From Music Data Analysis
to Industrial Quality Improvement, Springer International Publishing, 2019.
date_created: 2023-08-04T07:43:09Z
date_updated: 2023-10-16T13:07:21Z
department:
- _id: '34'
- _id: '819'
language:
- iso: eng
publication_identifier:
isbn:
- 978-3-030-25147-5
publisher: Springer International Publishing
series_title: Studies in Classification, Data Analysis, and Knowledge Organization
status: public
title: Applications in Statistical Computing — From Music Data Analysis to Industrial
Quality Improvement
type: book
user_id: '15504'
year: '2019'
...
---
_id: '46346'
abstract:
- lang: eng
text: In this article, we build upon previous work on designing informative and
efficient Exploratory Landscape Analysis features for characterizing problems'
landscapes and show their effectiveness in automatically constructing algorithm
selection models in continuous black-box optimization problems. Focusing on algorithm
performance results of the COCO platform of several years, we construct a representative
set of high-performing complementary solvers and present an algorithm selection
model that, compared to the portfolio's single best solver, on average requires
less than half of the resources for solving a given problem. Therefore, there
is a huge gain in efficiency compared to classical ensemble methods combined with
an increased insight into problem characteristics and algorithm properties by
using informative features. The model acts on the assumption that the function
set of the Black-Box Optimization Benchmark is representative enough for practical
applications. The model allows for selecting the best suited optimization algorithm
within the considered set for unseen problems prior to the optimization itself
based on a small sample of function evaluations. Note that such a sample can even
be reused for the initial population of an evolutionary (optimization) algorithm
so that even the feature costs become negligible.
author:
- first_name: Pascal
full_name: Kerschke, Pascal
last_name: Kerschke
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: Kerschke P, Trautmann H. Automated Algorithm Selection on Continuous Black-Box
Problems By Combining Exploratory Landscape Analysis and Machine Learning. Evolutionary
Computation (ECJ). 2019;27(1):99–127. doi:10.1162/evco_a_00236
apa: Kerschke, P., & Trautmann, H. (2019). Automated Algorithm Selection on
Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and
Machine Learning. Evolutionary Computation (ECJ), 27(1), 99–127.
https://doi.org/10.1162/evco_a_00236
bibtex: '@article{Kerschke_Trautmann_2019, title={Automated Algorithm Selection
on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and
Machine Learning}, volume={27}, DOI={10.1162/evco_a_00236},
number={1}, journal={Evolutionary Computation (ECJ)}, author={Kerschke, Pascal
and Trautmann, Heike}, year={2019}, pages={99–127} }'
chicago: 'Kerschke, Pascal, and Heike Trautmann. “Automated Algorithm Selection
on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and
Machine Learning.” Evolutionary Computation (ECJ) 27, no. 1 (2019): 99–127.
https://doi.org/10.1162/evco_a_00236.'
ieee: 'P. Kerschke and H. Trautmann, “Automated Algorithm Selection on Continuous
Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning,”
Evolutionary Computation (ECJ), vol. 27, no. 1, pp. 99–127, 2019, doi:
10.1162/evco_a_00236.'
mla: Kerschke, Pascal, and Heike Trautmann. “Automated Algorithm Selection on Continuous
Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning.”
Evolutionary Computation (ECJ), vol. 27, no. 1, 2019, pp. 99–127, doi:10.1162/evco_a_00236.
short: P. Kerschke, H. Trautmann, Evolutionary Computation (ECJ) 27 (2019) 99–127.
date_created: 2023-08-04T07:51:18Z
date_updated: 2023-10-16T13:31:57Z
department:
- _id: '34'
- _id: '819'
doi: 10.1162/evco_a_00236
intvolume: ' 27'
issue: '1'
language:
- iso: eng
page: 99–127
publication: Evolutionary Computation (ECJ)
status: public
title: Automated Algorithm Selection on Continuous Black-Box Problems By Combining
Exploratory Landscape Analysis and Machine Learning
type: journal_article
user_id: '15504'
volume: 27
year: '2019'
...