---
_id: '10213'
author:
- first_name: Vitaly
full_name: Melnikov, Vitaly
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics. In: Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017. ; 2017:1-12.'
apa: 'Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics. In Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017 (pp. 1–12).'
bibtex: '@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure
of Nested Dichotomies: A Comparison of Two Heuristics}, booktitle={Proceedings
27. Workshop Computational Intelligence, Dortmund, Germany 2017}, author={Melnikov,
Vitaly and Hüllermeier, Eyke}, year={2017}, pages={1–12} }'
chicago: 'Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics.” In Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 1–12, 2017.'
ieee: 'V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies:
A Comparison of Two Heuristics,” in Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.'
mla: 'Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested
Dichotomies: A Comparison of Two Heuristics.” Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.'
short: 'V. Melnikov, E. Hüllermeier, in: Proceedings 27. Workshop Computational
Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.'
date_created: 2019-06-07T15:49:36Z
date_updated: 2022-01-06T06:50:31Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
page: 1-12
publication: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany
2017
status: public
title: 'Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics'
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10216'
author:
- first_name: Ammar
full_name: Shaker, Ammar
last_name: Shaker
- first_name: W.
full_name: Heldt, W.
last_name: Heldt
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Shaker A, Heldt W, Hüllermeier E. Learning TSK Fuzzy Rules from Data Streams.
In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge
Discovery in Databases, Skopje, Macedonia. ; 2017.'
apa: Shaker, A., Heldt, W., & Hüllermeier, E. (2017). Learning TSK Fuzzy Rules
from Data Streams. In Proceedings ECML/PKDD, European Conference on Machine
Learning and Knowledge Discovery in Databases, Skopje, Macedonia.
bibtex: '@inproceedings{Shaker_Heldt_Hüllermeier_2017, title={Learning TSK Fuzzy
Rules from Data Streams}, booktitle={Proceedings ECML/PKDD, European Conference
on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia},
author={Shaker, Ammar and Heldt, W. and Hüllermeier, Eyke}, year={2017} }'
chicago: Shaker, Ammar, W. Heldt, and Eyke Hüllermeier. “Learning TSK Fuzzy Rules
from Data Streams.” In Proceedings ECML/PKDD, European Conference on Machine
Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
ieee: A. Shaker, W. Heldt, and E. Hüllermeier, “Learning TSK Fuzzy Rules from Data
Streams,” in Proceedings ECML/PKDD, European Conference on Machine Learning
and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
mla: Shaker, Ammar, et al. “Learning TSK Fuzzy Rules from Data Streams.” Proceedings
ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in
Databases, Skopje, Macedonia, 2017.
short: 'A. Shaker, W. Heldt, E. Hüllermeier, in: Proceedings ECML/PKDD, European
Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia,
2017.'
date_created: 2019-06-07T16:00:10Z
date_updated: 2022-01-06T06:50:32Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge
Discovery in Databases, Skopje, Macedonia
status: public
title: Learning TSK Fuzzy Rules from Data Streams
type: conference
user_id: '49109'
year: '2017'
...
---
_id: '10267'
author:
- first_name: M.
full_name: Bräuning, M.
last_name: Bräuning
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: T.
full_name: Keller, T.
last_name: Keller
- first_name: M.
full_name: Glaum, M.
last_name: Glaum
citation:
ama: Bräuning M, Hüllermeier E, Keller T, Glaum M. Lexicographic preferences for
predictive modeling of human decision making. A new machine learning method with
an application in accounting. European Journal of Operational Research.
2017;258(1):295-306.
apa: Bräuning, M., Hüllermeier, E., Keller, T., & Glaum, M. (2017). Lexicographic
preferences for predictive modeling of human decision making. A new machine learning
method with an application in accounting. European Journal of Operational
Research, 258(1), 295–306.
bibtex: '@article{Bräuning_Hüllermeier_Keller_Glaum_2017, title={Lexicographic preferences
for predictive modeling of human decision making. A new machine learning method
with an application in accounting}, volume={258}, number={1}, journal={European
Journal of Operational Research}, author={Bräuning, M. and Hüllermeier, Eyke and
Keller, T. and Glaum, M.}, year={2017}, pages={295–306} }'
chicago: 'Bräuning, M., Eyke Hüllermeier, T. Keller, and M. Glaum. “Lexicographic
Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning
Method with an Application in Accounting.” European Journal of Operational
Research 258, no. 1 (2017): 295–306.'
ieee: M. Bräuning, E. Hüllermeier, T. Keller, and M. Glaum, “Lexicographic preferences
for predictive modeling of human decision making. A new machine learning method
with an application in accounting,” European Journal of Operational Research,
vol. 258, no. 1, pp. 295–306, 2017.
mla: Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of
Human Decision Making. A New Machine Learning Method with an Application in Accounting.”
European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306.
short: M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational
Research 258 (2017) 295–306.
date_created: 2019-06-18T15:43:40Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 258'
issue: '1'
language:
- iso: eng
page: 295-306
publication: European Journal of Operational Research
status: public
title: Lexicographic preferences for predictive modeling of human decision making.
A new machine learning method with an application in accounting
type: journal_article
user_id: '49109'
volume: 258
year: '2017'
...
---
_id: '10268'
author:
- first_name: M.-C.
full_name: Platenius, M.-C.
last_name: Platenius
- first_name: Ammar
full_name: Shaker, Ammar
last_name: Shaker
- first_name: M.
full_name: Becker, M.
last_name: Becker
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: W.
full_name: Schäfer, W.
last_name: Schäfer
citation:
ama: Platenius M-C, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching
of Requirements Specifications for Software Services Using Fuzzy Logic. IEEE
Transactions on Software Engineering. 2017;43(8):739-759.
apa: Platenius, M.-C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W.
(2017). Imprecise Matching of Requirements Specifications for Software Services
Using Fuzzy Logic. IEEE Transactions on Software Engineering, 43(8),
739–759.
bibtex: '@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2017, title={Imprecise
Matching of Requirements Specifications for Software Services Using Fuzzy Logic},
volume={43}, number={8}, journal={IEEE Transactions on Software Engineering},
author={Platenius, M.-C. and Shaker, Ammar and Becker, M. and Hüllermeier, Eyke
and Schäfer, W.}, year={2017}, pages={739–759} }'
chicago: 'Platenius, M.-C., Ammar Shaker, M. Becker, Eyke Hüllermeier, and W. Schäfer.
“Imprecise Matching of Requirements Specifications for Software Services Using
Fuzzy Logic.” IEEE Transactions on Software Engineering 43, no. 8 (2017):
739–59.'
ieee: M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise
Matching of Requirements Specifications for Software Services Using Fuzzy Logic,”
IEEE Transactions on Software Engineering, vol. 43, no. 8, pp. 739–759,
2017.
mla: Platenius, M. C., et al. “Imprecise Matching of Requirements Specifications
for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering,
vol. 43, no. 8, 2017, pp. 739–59.
short: M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions
on Software Engineering 43 (2017) 739–759.
date_created: 2019-06-18T15:47:33Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
intvolume: ' 43'
issue: '8'
language:
- iso: eng
page: 739-759
publication: IEEE Transactions on Software Engineering
status: public
title: Imprecise Matching of Requirements Specifications for Software Services Using
Fuzzy Logic
type: journal_article
user_id: '49109'
volume: 43
year: '2017'
...
---
_id: '10269'
article_number: 'abs/1712.00646 '
author:
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Hüllermeier E. From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based
Systems: A Critical Reflection. The Computing Research Repository (CoRR).
2017.'
apa: 'Hüllermeier, E. (2017). From Knowledge-based to Data-driven Modeling of Fuzzy
Rule-based Systems: A Critical Reflection. The Computing Research Repository
(CoRR).'
bibtex: '@article{Hüllermeier_2017, title={From Knowledge-based to Data-driven Modeling
of Fuzzy Rule-based Systems: A Critical Reflection}, number={abs/1712.00646},
journal={The Computing Research Repository (CoRR)}, author={Hüllermeier, Eyke},
year={2017} }'
chicago: 'Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy
Rule-Based Systems: A Critical Reflection.” The Computing Research Repository
(CoRR), 2017.'
ieee: 'E. Hüllermeier, “From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based
Systems: A Critical Reflection,” The Computing Research Repository (CoRR),
2017.'
mla: 'Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy
Rule-Based Systems: A Critical Reflection.” The Computing Research Repository
(CoRR), abs/1712.00646, 2017.'
short: E. Hüllermeier, The Computing Research Repository (CoRR) (2017).
date_created: 2019-06-18T15:53:28Z
date_updated: 2022-01-06T06:50:33Z
department:
- _id: '34'
- _id: '7'
- _id: '355'
language:
- iso: eng
publication: The Computing Research Repository (CoRR)
status: public
title: 'From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems:
A Critical Reflection'
type: journal_article
user_id: '49109'
year: '2017'
...
---
_id: '24154'
author:
- first_name: Arunselvan
full_name: Ramaswamy, Arunselvan
id: '66937'
last_name: Ramaswamy
orcid: https://orcid.org/ 0000-0001-7547-8111
- first_name: Shalabh
full_name: Bhatnagar, Shalabh
last_name: Bhatnagar
citation:
ama: Ramaswamy A, Bhatnagar S. Stochastic recursive inclusion in two timescales
with an application to the lagrangian dual problem. Stochastics. 2016;88(8):1173-1187.
apa: Ramaswamy, A., & Bhatnagar, S. (2016). Stochastic recursive inclusion in
two timescales with an application to the lagrangian dual problem. Stochastics,
88(8), 1173–1187.
bibtex: '@article{Ramaswamy_Bhatnagar_2016, title={Stochastic recursive inclusion
in two timescales with an application to the lagrangian dual problem}, volume={88},
number={8}, journal={Stochastics}, publisher={Taylor \& Francis}, author={Ramaswamy,
Arunselvan and Bhatnagar, Shalabh}, year={2016}, pages={1173–1187} }'
chicago: 'Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion
in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics
88, no. 8 (2016): 1173–87.'
ieee: A. Ramaswamy and S. Bhatnagar, “Stochastic recursive inclusion in two timescales
with an application to the lagrangian dual problem,” Stochastics, vol.
88, no. 8, pp. 1173–1187, 2016.
mla: Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion
in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics,
vol. 88, no. 8, Taylor \& Francis, 2016, pp. 1173–87.
short: A. Ramaswamy, S. Bhatnagar, Stochastics 88 (2016) 1173–1187.
date_created: 2021-09-10T10:21:49Z
date_updated: 2022-01-06T06:56:08Z
department:
- _id: '355'
extern: '1'
intvolume: ' 88'
issue: '8'
language:
- iso: eng
page: 1173-1187
publication: Stochastics
publisher: Taylor \& Francis
status: public
title: Stochastic recursive inclusion in two timescales with an application to the
lagrangian dual problem
type: journal_article
user_id: '66937'
volume: 88
year: '2016'
...
---
_id: '3318'
author:
- first_name: Vitalik
full_name: Melnikov, Vitalik
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Daniel
full_name: Kaimann, Daniel
id: '18949'
last_name: Kaimann
- first_name: 'Bernd '
full_name: 'Frick, Bernd '
last_name: Frick
- first_name: ' Pritha '
full_name: 'Gupta, Pritha '
last_name: Gupta
citation:
ama: 'Melnikov V, Hüllermeier E, Kaimann D, Frick B, Gupta Pritha . Pairwise versus
Pointwise Ranking: A Case Study. Schedae Informaticae. 2016;25. doi:10.4467/20838476si.16.006.6187'
apa: 'Melnikov, V., Hüllermeier, E., Kaimann, D., Frick, B., & Gupta, Pritha
. (2016). Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae,
25. https://doi.org/10.4467/20838476si.16.006.6187'
bibtex: '@article{Melnikov_Hüllermeier_Kaimann_Frick_Gupta_2016, title={Pairwise
versus Pointwise Ranking: A Case Study}, volume={25}, DOI={10.4467/20838476si.16.006.6187},
journal={Schedae Informaticae}, publisher={Uniwersytet Jagiellonski - Wydawnictwo
Uniwersytetu Jagiellonskiego}, author={Melnikov, Vitalik and Hüllermeier, Eyke
and Kaimann, Daniel and Frick, Bernd and Gupta, Pritha }, year={2016} }'
chicago: 'Melnikov, Vitalik, Eyke Hüllermeier, Daniel Kaimann, Bernd Frick, and Pritha Gupta.
“Pairwise versus Pointwise Ranking: A Case Study.” Schedae Informaticae
25 (2016). https://doi.org/10.4467/20838476si.16.006.6187.'
ieee: 'V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, and Pritha Gupta, “Pairwise
versus Pointwise Ranking: A Case Study,” Schedae Informaticae, vol. 25,
2016.'
mla: 'Melnikov, Vitalik, et al. “Pairwise versus Pointwise Ranking: A Case Study.”
Schedae Informaticae, vol. 25, Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu
Jagiellonskiego, 2016, doi:10.4467/20838476si.16.006.6187.'
short: V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, Pritha Gupta, Schedae
Informaticae 25 (2016).
date_created: 2018-06-22T14:49:40Z
date_updated: 2022-01-06T06:59:10Z
ddc:
- '000'
department:
- _id: '355'
- _id: '183'
doi: 10.4467/20838476si.16.006.6187
file:
- access_level: closed
content_type: application/pdf
creator: ups
date_created: 2018-11-02T15:54:38Z
date_updated: 2018-11-02T15:54:38Z
file_id: '5317'
file_name: roz-6-Melnikov.pdf
file_size: 1002478
relation: main_file
success: 1
file_date_updated: 2018-11-02T15:54:38Z
has_accepted_license: '1'
intvolume: ' 25'
language:
- iso: eng
project:
- _id: '3'
name: SFB 901 - Project Area B
- _id: '11'
name: SFB 901 - Subproject B3
- _id: '8'
name: SFB 901 - Subproject A4
- _id: '1'
name: SFB 901
- _id: '2'
name: SFB 901 - Project Area A
publication: Schedae Informaticae
publication_identifier:
issn:
- 2083-8476
publication_status: published
publisher: Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego
status: public
title: 'Pairwise versus Pointwise Ranking: A Case Study'
type: journal_article
user_id: '15504'
volume: 25
year: '2016'
...
---
_id: '190'
abstract:
- lang: eng
text: Today, software components are provided by global markets in the form of services.
In order to optimally satisfy service requesters and service providers, adequate
techniques for automatic service matching are needed. However, a requester’s requirements
may be vague and the information available about a provided service may be incomplete.
As a consequence, fuzziness is induced into the matching procedure. The contribution
of this paper is the development of a systematic matching procedure that leverages
concepts and techniques from fuzzy logic and possibility theory based on our formal
distinction between different sources and types of fuzziness in the context of
service matching. In contrast to existing methods, our approach is able to deal
with imprecision and incompleteness in service specifications and to inform users
about the extent of induced fuzziness in order to improve the user’s decision-making.
We demonstrate our approach on the example of specifications for service reputation
based on ratings given by previous users. Our evaluation based on real service
ratings shows the utility and applicability of our approach.
author:
- first_name: Marie Christin
full_name: Platenius, Marie Christin
last_name: Platenius
- first_name: Ammar
full_name: Shaker, Ammar
last_name: Shaker
- first_name: Matthias
full_name: Becker, Matthias
last_name: Becker
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
- first_name: Wilhelm
full_name: Schäfer, Wilhelm
last_name: Schäfer
citation:
ama: Platenius MC, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching
of Requirements Specifications for Software Services using Fuzzy Logic. IEEE
Transactions on Software Engineering (TSE), presented at ICSE 2017. 2016;(8):739-759.
doi:10.1109/TSE.2016.2632115
apa: Platenius, M. C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W.
(2016). Imprecise Matching of Requirements Specifications for Software Services
using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), Presented
at ICSE 2017, (8), 739–759. https://doi.org/10.1109/TSE.2016.2632115
bibtex: '@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2016, title={Imprecise
Matching of Requirements Specifications for Software Services using Fuzzy Logic},
DOI={10.1109/TSE.2016.2632115},
number={8}, journal={IEEE Transactions on Software Engineering (TSE), presented
at ICSE 2017}, publisher={IEEE}, author={Platenius, Marie Christin and Shaker,
Ammar and Becker, Matthias and Hüllermeier, Eyke and Schäfer, Wilhelm}, year={2016},
pages={739–759} }'
chicago: 'Platenius, Marie Christin, Ammar Shaker, Matthias Becker, Eyke Hüllermeier,
and Wilhelm Schäfer. “Imprecise Matching of Requirements Specifications for Software
Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering (TSE),
Presented at ICSE 2017, no. 8 (2016): 739–59. https://doi.org/10.1109/TSE.2016.2632115.'
ieee: M. C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise
Matching of Requirements Specifications for Software Services using Fuzzy Logic,”
IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017,
no. 8, pp. 739–759, 2016.
mla: Platenius, Marie Christin, et al. “Imprecise Matching of Requirements Specifications
for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering
(TSE), Presented at ICSE 2017, no. 8, IEEE, 2016, pp. 739–59, doi:10.1109/TSE.2016.2632115.
short: M.C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions
on Software Engineering (TSE), Presented at ICSE 2017 (2016) 739–759.
date_created: 2017-10-17T12:41:29Z
date_updated: 2022-01-06T06:53:57Z
ddc:
- '040'
department:
- _id: '355'
doi: 10.1109/TSE.2016.2632115
file:
- access_level: closed
content_type: application/pdf
creator: florida
date_created: 2018-03-21T12:30:31Z
date_updated: 2018-03-21T12:30:31Z
file_id: '1529'
file_name: 190-07755807.pdf
file_size: 5225413
relation: main_file
success: 1
file_date_updated: 2018-03-21T12:30:31Z
has_accepted_license: '1'
issue: '8'
language:
- iso: eng
page: 739-759
project:
- _id: '1'
name: SFB 901
- _id: '9'
name: SFB 901 - Subprojekt B1
- _id: '10'
name: SFB 901 - Subprojekt B2
- _id: '11'
name: SFB 901 - Subprojekt B3
- _id: '3'
name: SFB 901 - Project Area B
publication: IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017
publisher: IEEE
status: public
title: Imprecise Matching of Requirements Specifications for Software Services using
Fuzzy Logic
type: journal_article
user_id: '15504'
year: '2016'
...
---
_id: '184'
abstract:
- lang: eng
text: In this paper, we propose a framework for a class of learning problems that
we refer to as “learning to aggregate”. Roughly, learning-to-aggregate problems
are supervised machine learning problems, in which instances are represented in
the form of a composition of a (variable) number on constituents; such compositions
are associated with an evaluation, score, or label, which is the target of the
prediction task, and which can presumably be modeled in the form of a suitable
aggregation of the properties of its constituents. Our learning-to-aggregate framework
establishes a close connection between machine learning and a branch of mathematics
devoted to the systematic study of aggregation functions. We specifically focus
on a class of functions called uninorms, which combine conjunctive and disjunctive
modes of aggregation. Experimental results for a corresponding model are presented
for a review data set, for which the aggregation problem consists of combining
different reviewer opinions about a paper into an overall decision of acceptance
or rejection.
author:
- first_name: Vitaly
full_name: Melnikov, Vitaly
id: '58747'
last_name: Melnikov
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Melnikov V, Hüllermeier E. Learning to Aggregate Using Uninorms. In: Proceedings
of the Joint European Conference on Machine Learning and Knowledge Discovery in
Databases (ECML/PKDD 2016). LNCS. ; 2016:756-771. doi:10.1007/978-3-319-46227-1_47'
apa: Melnikov, V., & Hüllermeier, E. (2016). Learning to Aggregate Using Uninorms.
In Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016) (pp. 756–771). https://doi.org/10.1007/978-3-319-46227-1_47
bibtex: '@inproceedings{Melnikov_Hüllermeier_2016, series={LNCS}, title={Learning
to Aggregate Using Uninorms}, DOI={10.1007/978-3-319-46227-1_47},
booktitle={Proceedings of the Joint European Conference on Machine Learning and
Knowledge Discovery in Databases (ECML/PKDD 2016)}, author={Melnikov, Vitaly and
Hüllermeier, Eyke}, year={2016}, pages={756–771}, collection={LNCS} }'
chicago: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.”
In Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016), 756–71. LNCS, 2016. https://doi.org/10.1007/978-3-319-46227-1_47.
ieee: V. Melnikov and E. Hüllermeier, “Learning to Aggregate Using Uninorms,” in
Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.
mla: Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.”
Proceedings of the Joint European Conference on Machine Learning and Knowledge
Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–71, doi:10.1007/978-3-319-46227-1_47.
short: 'V. Melnikov, E. Hüllermeier, in: Proceedings of the Joint European Conference
on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016,
pp. 756–771.'
date_created: 2017-10-17T12:41:27Z
date_updated: 2022-01-06T06:53:32Z
ddc:
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doi: 10.1007/978-3-319-46227-1_47
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publication: Proceedings of the Joint European Conference on Machine Learning and
Knowledge Discovery in Databases (ECML/PKDD 2016)
series_title: LNCS
status: public
title: Learning to Aggregate Using Uninorms
type: conference
user_id: '15504'
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...
---
_id: '10785'
author:
- first_name: J.
full_name: Fürnkranz, J.
last_name: Fürnkranz
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: 'Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds.
Encyclopedia of Machine Learning and Data Mining. Springer; 2016.'
apa: Fürnkranz, J., & Hüllermeier, E. (2016). Preference Learning. In C. Sammut
& G. I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining.
Springer.
bibtex: '@inbook{Fürnkranz_Hüllermeier_2016, title={Preference Learning}, booktitle={Encyclopedia
of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz,
J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2016}
}'
chicago: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb. Springer,
2016.
ieee: J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in Encyclopedia
of Machine Learning and Data Mining, C. Sammut and G. I. Webb, Eds. Springer,
2016.
mla: Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” Encyclopedia
of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, Springer,
2016.
short: 'J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia
of Machine Learning and Data Mining, Springer, 2016.'
date_created: 2019-07-10T16:00:23Z
date_updated: 2022-01-06T06:50:50Z
department:
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editor:
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full_name: Sammut, C.
last_name: Sammut
- first_name: G.I.
full_name: Webb, G.I.
last_name: Webb
language:
- iso: eng
publication: Encyclopedia of Machine Learning and Data Mining
publisher: Springer
status: public
title: Preference Learning
type: encyclopedia_article
user_id: '49109'
year: '2016'
...