{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T17:15:31Z","timestamp":1758820531146,"version":"3.40.3"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031124259"},{"type":"electronic","value":"9783031124266"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-031-12426-6_29","type":"book-chapter","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T16:10:03Z","timestamp":1659024603000},"page":"310-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Quasi-Clique Mining for\u00a0Graph Summarization"],"prefix":"10.1007","author":[{"given":"Antoine","family":"Castillon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julien","family":"Baste","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hamida","family":"Seba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Haddad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,29]]},"reference":[{"unstructured":"Ahmad, M., Beg, M.A., Khan, I., Zaman, A., Khan, M.A.: SsAG: Summarization and sparsification of attributed graphs (2021)","key":"29_CR1"},{"doi-asserted-by":"crossref","unstructured":"Baril, A., Dondi, R., Hosseinzadeh, M.M.: Hardness and tractability of the $$\\gamma $$-complete subgraph problem. Inf. Process. Lett. 169, 106105 (2021)","key":"29_CR2","DOI":"10.1016\/j.ipl.2021.106105"},{"doi-asserted-by":"crossref","unstructured":"Boldi, P., Vigna, S.: The webgraph framework i: Compression techniques. In: Proceedings of WWW2004. pp. 595\u2013602 (2004)","key":"29_CR3","DOI":"10.1145\/988672.988752"},{"doi-asserted-by":"crossref","unstructured":"Lagraa, S., Seba, H., Khennoufa, R., MBaya, A., Kheddouci, H.: a distance measure for large graphs based on prime graphs. Pattern Recogn. 47(9), 2993\u20133005 (2014)","key":"29_CR4","DOI":"10.1016\/j.patcog.2014.03.014"},{"doi-asserted-by":"crossref","unstructured":"Lee, K., Jo, H., Ko, J., Lim, S., Shin, K.: SSumM Sparse summarization of massive graphs. In: Proceedings of the 26th ACM SIGKDD. pp. 144\u2013154 (2020)","key":"29_CR5","DOI":"10.1145\/3394486.3403057"},{"unstructured":"Leskovec, J., Krevl, A.: SNAP datasets: stanford large network dataset collection (2014). http:\/\/snap.stanford.edu\/data","key":"29_CR6"},{"doi-asserted-by":"publisher","unstructured":"Liu, G., Wong, L.: Effective pruning techniques for mining quasi-cliques. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008. LNCS (LNAI), vol. 5212, pp. 33\u201349. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-87481-2_3","key":"29_CR7","DOI":"10.1007\/978-3-540-87481-2_3"},{"doi-asserted-by":"crossref","unstructured":"Navlakha, S., Rastogi, R., Shrivastava, N.: Graph summarization with bounded error. In: Proceedings of the 2008 ACM SIGMOD Conference. pp. 419\u2013432 (2008)","key":"29_CR8","DOI":"10.1145\/1376616.1376661"},{"doi-asserted-by":"crossref","unstructured":"Wang, J., Cheng, J., Fu, A.W.C.: Redundancy-aware maximal cliques. In: Proceedings of the 19th ACM SIGKDD Conference. pp. 122\u2013130 (2013)","key":"29_CR9","DOI":"10.1145\/2487575.2487689"},{"doi-asserted-by":"crossref","unstructured":"Wang, L., Lu, Y., Jiang, B., Gao, K.T., Zhou, T.H.: Dense subgraphs summarization: an efficient way to summarize large scale graphs by super nodes. In: 16th International Conference on Intelligent Computing Methodologies, Italy. pp. 520\u2013530 (2020)","key":"29_CR10","DOI":"10.1007\/978-3-030-60796-8_45"}],"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\/978-3-031-12426-6_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T11:30:14Z","timestamp":1710329414000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-12426-6_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031124259","9783031124266"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-12426-6_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"29 July 2022","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":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 August 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"33","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dexa2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dexa.org\/dexa2022","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-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":"120","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":"43","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":"36% - 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":"5","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":"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":"Mixed review process- Single and double blind","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)"}}]}}