---
_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: <i>Proceedings of the 30th ACM Conference on Hypertext and Social Media  -
    HT ’19</i>. ACM; 2019:163-171. doi:<a href="https://doi.org/10.1145/3342220.3343660">10.1145/3342220.3343660</a>'
  apa: Desouki, A. A., Röder, M., &#38; Ngonga Ngomo, A.-C. (2019). Ranking on Very
    Large Knowledge Graphs. In <i>Proceedings of the 30th ACM Conference on Hypertext
    and Social Media  - HT ’19</i> (pp. 163–171). ACM. <a href="https://doi.org/10.1145/3342220.3343660">https://doi.org/10.1145/3342220.3343660</a>
  bibtex: '@inproceedings{Desouki_Röder_Ngonga Ngomo_2019, title={Ranking on Very
    Large Knowledge Graphs}, DOI={<a href="https://doi.org/10.1145/3342220.3343660">10.1145/3342220.3343660</a>},
    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 <i>Proceedings of the 30th ACM Conference
    on Hypertext and Social Media  - HT ’19</i>, 163–71. ACM, 2019. <a href="https://doi.org/10.1145/3342220.3343660">https://doi.org/10.1145/3342220.3343660</a>.
  ieee: A. A. Desouki, M. Röder, and A.-C. Ngonga Ngomo, “Ranking on Very Large Knowledge
    Graphs,” in <i>Proceedings of the 30th ACM Conference on Hypertext and Social
    Media  - HT ’19</i>, 2019, pp. 163–171.
  mla: Desouki, Abdelmoneim Amer, et al. “Ranking on Very Large Knowledge Graphs.”
    <i>Proceedings of the 30th ACM Conference on Hypertext and Social Media  - HT
    ’19</i>, ACM, 2019, pp. 163–71, doi:<a href="https://doi.org/10.1145/3342220.3343660">10.1145/3342220.3343660</a>.
  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'
...