---
_id: '15921'
abstract:
- lang: eng
text: "Ranking plays a central role in a large number of applications driven by
RDF knowledge graphs. Over the last years, many popular RDF knowledge graphs have
grown so large that rankings for the facts they contain cannot be computed directly
using the currently common 64-bit platforms. In this paper, we tackle two problems:\r\nComputing
ranks on such large knowledge bases efficiently and incrementally. First, we present
D-HARE, a distributed approach for computing ranks on very large knowledge graphs.
D-HARE assumes the random surfer model and relies on data partitioning to compute
matrix multiplications and transpositions on disk for matrices of arbitrary size.
Moreover, the data partitioning underlying D-HARE allows the execution of most
of its steps in parallel.\r\nAs very large knowledge graphs are often updated
periodically, we tackle the incremental computation of ranks on large knowledge
bases as a second problem. We address this problem by presenting\r\nI-HARE, an
approximation technique for calculating the overall ranking scores of a knowledge
without the need to recalculate the ranking from scratch at each new revision.
We evaluate our approaches by calculating ranks on the 3 × 10^9 and 2.4 × 10^9
triples from Wikidata resp. LinkedGeoData. Our evaluation demonstrates\r\nthat
D-HARE is the first holistic approach for computing ranks on very large RDF knowledge
graphs. In addition, our incremental approach achieves a root mean squared error
of less than 10E−7 in the best case. Both D-HARE\r\n and I-HARE are open-source
and are available at: https://github.com/dice-group/incrementalHARE.\r\n"
author:
- first_name: Abdelmoneim Amer
full_name: Desouki, Abdelmoneim Amer
last_name: Desouki
- first_name: Michael
full_name: Röder, Michael
last_name: Röder
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
last_name: Ngonga Ngomo
citation:
ama: 'Desouki AA, Röder M, Ngonga Ngomo A-C. Ranking on Very Large Knowledge Graphs.
In: Proceedings of the 30th ACM Conference on Hypertext and Social Media -
HT ’19. ACM; 2019:163-171. doi:10.1145/3342220.3343660'
apa: Desouki, A. A., Röder, M., & Ngonga Ngomo, A.-C. (2019). Ranking on Very
Large Knowledge Graphs. In Proceedings of the 30th ACM Conference on Hypertext
and Social Media - HT ’19 (pp. 163–171). ACM. https://doi.org/10.1145/3342220.3343660
bibtex: '@inproceedings{Desouki_Röder_Ngonga Ngomo_2019, title={Ranking on Very
Large Knowledge Graphs}, DOI={10.1145/3342220.3343660},
booktitle={Proceedings of the 30th ACM Conference on Hypertext and Social Media
- HT ’19}, publisher={ACM}, author={Desouki, Abdelmoneim Amer and Röder, Michael
and Ngonga Ngomo, Axel-Cyrille}, year={2019}, pages={163–171} }'
chicago: Desouki, Abdelmoneim Amer, Michael Röder, and Axel-Cyrille Ngonga Ngomo.
“Ranking on Very Large Knowledge Graphs.” In Proceedings of the 30th ACM Conference
on Hypertext and Social Media - HT ’19, 163–71. ACM, 2019. https://doi.org/10.1145/3342220.3343660.
ieee: A. A. Desouki, M. Röder, and A.-C. Ngonga Ngomo, “Ranking on Very Large Knowledge
Graphs,” in Proceedings of the 30th ACM Conference on Hypertext and Social
Media - HT ’19, 2019, pp. 163–171.
mla: Desouki, Abdelmoneim Amer, et al. “Ranking on Very Large Knowledge Graphs.”
Proceedings of the 30th ACM Conference on Hypertext and Social Media - HT
’19, ACM, 2019, pp. 163–71, doi:10.1145/3342220.3343660.
short: 'A.A. Desouki, M. Röder, A.-C. Ngonga Ngomo, in: Proceedings of the 30th
ACM Conference on Hypertext and Social Media - HT ’19, ACM, 2019, pp. 163–171.'
conference:
end_date: 2019-09-20
name: 30th ACM Conference on Hypertext and Social Media
start_date: 2019-09-17
date_created: 2020-02-18T16:39:35Z
date_updated: 2022-01-06T06:52:41Z
department:
- _id: '574'
doi: 10.1145/3342220.3343660
keyword:
- Knowledge Graphs
- Ranking
- RDF
language:
- iso: eng
page: 163-171
project:
- _id: '52'
name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: Proceedings of the 30th ACM Conference on Hypertext and Social Media -
HT '19
publication_identifier:
isbn:
- '9781450368858'
publication_status: published
publisher: ACM
status: public
title: Ranking on Very Large Knowledge Graphs
type: conference
user_id: '69382'
year: '2019'
...
---
_id: '46405'
abstract:
- lang: eng
text: 'We present methods to answer two basic questions that arise when benchmarking
optimization algorithms. The first one is: which algorithm is the ’best’ one?
and the second one: which algorithm should I use for my real world problem? Both
are connected and neither is easy to answer. We present methods which can be used
to analyse the raw data of a benchmark experiment and derive some insight regarding
the answers to these questions. We employ the presented methods to analyse the
BBOB’09 benchmark results and present some initial findings.'
author:
- first_name: Olaf
full_name: Mersmann, Olaf
last_name: Mersmann
- first_name: Mike
full_name: Preuss, Mike
last_name: Preuss
- first_name: Heike
full_name: Trautmann, Heike
id: '100740'
last_name: Trautmann
orcid: 0000-0002-9788-8282
citation:
ama: 'Mersmann O, Preuss M, Trautmann H. Benchmarking Evolutionary Algorithms: Towards
Exploratory Landscape Analysis. In: Proceedings of the 11th International Conference
on Parallel Problem Solving from Nature: Part I. PPSN’10. Springer-Verlag;
2010:73–82.'
apa: 'Mersmann, O., Preuss, M., & Trautmann, H. (2010). Benchmarking Evolutionary
Algorithms: Towards Exploratory Landscape Analysis. Proceedings of the 11th
International Conference on Parallel Problem Solving from Nature: Part I,
73–82.'
bibtex: '@inproceedings{Mersmann_Preuss_Trautmann_2010, place={Berlin, Heidelberg},
series={PPSN’10}, title={Benchmarking Evolutionary Algorithms: Towards Exploratory
Landscape Analysis}, booktitle={Proceedings of the 11th International Conference
on Parallel Problem Solving from Nature: Part I}, publisher={Springer-Verlag},
author={Mersmann, Olaf and Preuss, Mike and Trautmann, Heike}, year={2010}, pages={73–82},
collection={PPSN’10} }'
chicago: 'Mersmann, Olaf, Mike Preuss, and Heike Trautmann. “Benchmarking Evolutionary
Algorithms: Towards Exploratory Landscape Analysis.” In Proceedings of the
11th International Conference on Parallel Problem Solving from Nature: Part I,
73–82. PPSN’10. Berlin, Heidelberg: Springer-Verlag, 2010.'
ieee: 'O. Mersmann, M. Preuss, and H. Trautmann, “Benchmarking Evolutionary Algorithms:
Towards Exploratory Landscape Analysis,” in Proceedings of the 11th International
Conference on Parallel Problem Solving from Nature: Part I, 2010, pp. 73–82.'
mla: 'Mersmann, Olaf, et al. “Benchmarking Evolutionary Algorithms: Towards Exploratory
Landscape Analysis.” Proceedings of the 11th International Conference on Parallel
Problem Solving from Nature: Part I, Springer-Verlag, 2010, pp. 73–82.'
short: 'O. Mersmann, M. Preuss, H. Trautmann, in: Proceedings of the 11th International
Conference on Parallel Problem Solving from Nature: Part I, Springer-Verlag, Berlin,
Heidelberg, 2010, pp. 73–82.'
date_created: 2023-08-04T16:02:28Z
date_updated: 2023-10-16T13:55:43Z
department:
- _id: '34'
- _id: '819'
keyword:
- benchmarking
- multidimensional scaling
- consensus ranking
- evolutionary optimization
- BBOB test set
language:
- iso: eng
page: 73–82
place: Berlin, Heidelberg
publication: 'Proceedings of the 11th International Conference on Parallel Problem
Solving from Nature: Part I'
publication_identifier:
isbn:
- '3642158439'
publisher: Springer-Verlag
series_title: PPSN’10
status: public
title: 'Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis'
type: conference
user_id: '15504'
year: '2010'
...