{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:39:41Z","timestamp":1742913581295,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030590024"},{"type":"electronic","value":"9783030590031"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-59003-1_4","type":"book-chapter","created":{"date-parts":[[2020,9,13]],"date-time":"2020-09-13T14:02:26Z","timestamp":1600005746000},"page":"55-70","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Accelerating All 5-Vertex Subgraphs Counting Using GPUs"],"prefix":"10.1007","author":[{"given":"Shuya","family":"Suganami","sequence":"first","affiliation":[]},{"given":"Toshiyuki","family":"Amagasa","sequence":"additional","affiliation":[]},{"given":"Hiroyuki","family":"Kitagawa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,9,14]]},"reference":[{"key":"4_CR1","unstructured":"Escape. https:\/\/bitbucket.org\/seshadhri\/escape"},{"key":"4_CR2","unstructured":"Openacc-standard.org. https:\/\/www.openacc.org\/sites\/default\/files\/inline-images\/Specification\/OpenACC.3.0.pdf"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Ahmed, N.K., Neville, J., Rossi, R.A., Duffield, N.: Efficient graphlet counting for large networks. In: 2015 IEEE International Conference on Data Mining, pp. 1\u201310. IEEE (2015)","DOI":"10.1109\/ICDM.2015.141"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Bhuiyan, M.A., Rahman, M., Rahman, M., Al Hasan, M.: Guise: uniform sampling of graphlets for large graph analysis. In: 2012 IEEE 12th International Conference on Data Mining, pp. 91\u2013100. IEEE (2012)","DOI":"10.1109\/ICDM.2012.87"},{"issue":"1","key":"4_CR5","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1137\/0214017","volume":"14","author":"N Chiba","year":"1985","unstructured":"Chiba, N., Nishizeki, T.: Arboricity and subgraph listing algorithms. SIAM J. Comput. 14(1), 210\u2013223 (1985)","journal-title":"SIAM J. Comput."},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Choobdar, S., Ribeiro, P., Bugla, S., Silva, F.: Comparison of co-authorship networks across scientific fields using motifs. In: 2012 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 147\u2013152. IEEE (2012)","DOI":"10.1109\/ASONAM.2012.34"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Durak, N., Pinar, A., Kolda, T.G., Seshadhri, C.: Degree relations of triangles in real-world networks and graph models. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, pp. 1712\u20131716 (2012)","DOI":"10.1145\/2396761.2398503"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Elenberg, E.R., Shanmugam, K., Borokhovich, M., Dimakis, A.G.: Distributed estimation of graph 4-profiles. In: Proceedings of the 25th International Conference on World Wide Web, pp. 483\u2013493 (2016)","DOI":"10.1145\/2872427.2883082"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Ho \u010d evar, T.\u017e., Dem \u0161 ar, J.: A combinatorial approach to graphlet counting. Bioinformatics 30(4), 559\u2013565 (2014)","DOI":"10.1093\/bioinformatics\/btt717"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Hayes, W., Sun, K., Pr \u017e ulj, N.\u0161.a.: Graphlet-based measures are suitable for biological network comparison. Bioinformatics 29(4), 483\u2013491 (2013)","DOI":"10.1093\/bioinformatics\/bts729"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Jha, M., Seshadhri, C., Pinar, A.: Path sampling: a fast and provable method for estimating 4-vertex subgraph counts. In: Proceedings of the 24th International Conference on World Wide Web, pp. 495\u2013505 (2015)","DOI":"10.1145\/2736277.2741101"},{"key":"4_CR12","unstructured":"Leskovec, J., Krevl, A.: SNAP Datasets : Stanford large network dataset collection. http:\/\/snap.stanford.edu\/data June 2014"},{"issue":"2","key":"4_CR13","doi-asserted-by":"publisher","first-page":"810","DOI":"10.1016\/j.comnet.2011.08.019","volume":"56","author":"D Marcus","year":"2012","unstructured":"Marcus, D., Shavitt, Y.: Rage-a rapid graphlet enumerator for large networks. Comput. Netw. 56(2), 810\u2013819 (2012)","journal-title":"Comput. Netw."},{"key":"4_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-319-28361-6_1","volume-title":"Advances in Network Science","author":"Mark Ortmann","year":"2016","unstructured":"Ortmann, Mark, Brandes, Ulrik: Quad census computation: simple, efficient, and orbit-aware. In: Wierzbicki, Adam, Brandes, Ulrik, Schweitzer, Frank, Pedreschi, Dino (eds.) NetSci-X 2016. LNCS, vol. 9564, pp. 1\u201313. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-28361-6_1"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Pinar, A., Seshadhri, C., Vishal, V.: Escape: efficiently counting all 5-vertex subgraphs. In: Proceedings of the 26th International Conference on World Wide Web, pp. 1431\u20131440. International World Wide Web Conferences Steering Committee (2017)","DOI":"10.1145\/3038912.3052597"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Rahman, M., Bhuiyan, M., Hasan, M.A.: Graft: an approximate graphlet counting algorithm for large graph analysis. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, pp. 1467\u20131471 (2012)","DOI":"10.1145\/2396761.2398454"},{"issue":"10","key":"4_CR17","doi-asserted-by":"publisher","first-page":"2466","DOI":"10.1109\/TKDE.2013.2297929","volume":"26","author":"M Rahman","year":"2014","unstructured":"Rahman, M., Bhuiyan, M.A., Al Hasan, M.: Graft: an efficient graphlet counting method for large graph analysis. IEEE Trans. Knowl. Data Eng. 26(10), 2466\u20132478 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"4_CR18","unstructured":"Ribeiro, P., Paredes, P., Silva, M.E., Aparicio, D., Silva, F.: A survey on subgraph counting: concepts, algorithms and applications to network motifs and graphlets. arXiv preprint arXiv:1910.13011 (2019)"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Rossi, R.A., Ahmed, N.K.: The network data repository with interactive graph analytics and visualization. In: AAAI (2015). http:\/\/networkrepository.com","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"4_CR20","doi-asserted-by":"crossref","unstructured":"Rossi, R.A., Zhou, R.: Leveraging multiple GPUS and CPUS for graphlet counting in large networks. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, pp. 1783\u20131792. ACM (2016)","DOI":"10.1145\/2983323.2983832"},{"issue":"4","key":"4_CR21","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1002\/minf.200900080","volume":"29","author":"M Rupp","year":"2010","unstructured":"Rupp, M., Schneider, G.: Graph kernels for molecular similarity. Molecular Inform. 29(4), 266\u2013273 (2010)","journal-title":"Molecular Inform."},{"key":"4_CR22","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1007\/11427186_54","volume-title":"Experimental and Efficient Algorithms","author":"Thomas Schank","year":"2005","unstructured":"Schank, Thomas, Wagner, Dorothea: Finding, counting and listing all triangles in large graphs, an experimental study. In: Nikoletseas, Sotiris E. (ed.) WEA 2005. LNCS, vol. 3503, pp. 606\u2013609. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11427186_54"},{"issue":"4","key":"4_CR23","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1016\/j.anbehav.2012.01.011","volume":"83","author":"D Shizuka","year":"2012","unstructured":"Shizuka, D., McDonald, D.B.: A social network perspective on measurements of dominance hierarchies. Animal Behav. 83(4), 925\u2013934 (2012)","journal-title":"Animal Behav."},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Sporns, O., K\u00f6tter, R.: Motifs in brain networks. PLoS Biology 2(11) 56\u201362 (2004)","DOI":"10.1371\/journal.pbio.0020369"},{"key":"4_CR25","doi-asserted-by":"crossref","unstructured":"Tsourakakis, C.E., Pachocki, J., Mitzenmacher, M.: Scalable motif-aware graph clustering. In: Proceedings of the 26th International Conference on World Wide Web, pp. 1451\u20131460 (2017)","DOI":"10.1145\/3038912.3052653"},{"issue":"1","key":"4_CR26","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/TKDE.2017.2756836","volume":"30","author":"P Wang","year":"2017","unstructured":"Wang, P., Zhao, J., Zhang, X., Li, Z., Cheng, J., Lui, J.C., Towsley, D., Tao, J., Guan, X.: Moss-5: a fast method of approximating counts of 5-node graphlets in large graphs. IEEE Trans. Knowl. Data Eng. 30(1), 73\u201386 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."}],"container-title":["Lecture Notes in Computer Science","Database and Expert Systems Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59003-1_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T14:17:51Z","timestamp":1710339471000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-59003-1_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030590024","9783030590031"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59003-1_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"14 September 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEXA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Database and Expert Systems Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bratislava","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Slovakia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/dexa2020","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"190","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4-6","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3-4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic the conference was held online. DEXA Workshops volume: submissions sent - 15, full papers accepted - 6, short papers accepted - 4, reviewers per paper 3, papers per reviewer 1-2","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}