[{"publication":"Proceedings of the 30th ACM Conference on Hypertext and Social Media  - HT '19","type":"conference","abstract":[{"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","lang":"eng"}],"status":"public","_id":"15921","project":[{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"department":[{"_id":"574"}],"user_id":"69382","keyword":["Knowledge Graphs","Ranking","RDF"],"language":[{"iso":"eng"}],"publication_identifier":{"isbn":["9781450368858"]},"publication_status":"published","year":"2019","page":"163-171","citation":{"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.","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} }","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>.","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>","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>","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.","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>."},"publisher":"ACM","date_updated":"2022-01-06T06:52:41Z","date_created":"2020-02-18T16:39:35Z","author":[{"full_name":"Desouki, Abdelmoneim Amer","last_name":"Desouki","first_name":"Abdelmoneim Amer"},{"last_name":"Röder","full_name":"Röder, Michael","first_name":"Michael"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"title":"Ranking on Very Large Knowledge Graphs","doi":"10.1145/3342220.3343660","conference":{"end_date":"2019-09-20","name":"30th ACM Conference on Hypertext and Social Media","start_date":"2019-09-17"}},{"title":"Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis","date_created":"2023-08-04T16:02:28Z","author":[{"full_name":"Mersmann, Olaf","last_name":"Mersmann","first_name":"Olaf"},{"first_name":"Mike","last_name":"Preuss","full_name":"Preuss, Mike"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike"}],"date_updated":"2023-10-16T13:55:43Z","publisher":"Springer-Verlag","citation":{"apa":"Mersmann, O., Preuss, M., &#38; Trautmann, H. (2010). Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, 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.","mla":"Mersmann, Olaf, et al. “Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis.” <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, Springer-Verlag, 2010, pp. 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 <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</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 <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>, 2010, pp. 73–82.","ama":"Mersmann O, Preuss M, Trautmann H. Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. In: <i>Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I</i>. PPSN’10. Springer-Verlag; 2010:73–82."},"page":"73–82","year":"2010","place":"Berlin, Heidelberg","publication_identifier":{"isbn":["3642158439"]},"language":[{"iso":"eng"}],"keyword":["benchmarking","multidimensional scaling","consensus ranking","evolutionary optimization","BBOB test set"],"series_title":"PPSN’10","user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"_id":"46405","status":"public","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."}],"type":"conference","publication":"Proceedings of the 11th International Conference on Parallel Problem Solving from Nature: Part I"}]