{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T15:54:24Z","timestamp":1743090864084,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031013324"},{"type":"electronic","value":"9783031013331"}],"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\/978-3-031-01333-1_15","type":"book-chapter","created":{"date-parts":[[2022,4,6]],"date-time":"2022-04-06T03:33:56Z","timestamp":1649216036000},"page":"185-198","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Selecting Outstanding Patterns Based on\u00a0Their Neighbourhood"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1374-5453","authenticated-orcid":false,"given":"Etienne","family":"Lehembre","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9404-8117","authenticated-orcid":false,"given":"Ronan","family":"Bureau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8294-9049","authenticated-orcid":false,"given":"Bruno","family":"Cremilleux","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4964-5427","authenticated-orcid":false,"given":"Bertrand","family":"Cuissart","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6493-1769","authenticated-orcid":false,"given":"Jean-Luc","family":"Lamotte","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0202-1588","authenticated-orcid":false,"given":"Alban","family":"Lepailleur","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0855-0181","authenticated-orcid":false,"given":"Abdelkader","family":"Ouali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8319-7456","authenticated-orcid":false,"given":"Albrecht","family":"Zimmermann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,7]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Besson, J., Rigotti, C., Mitasiunaite, I., Boulicaut, J.F.: Parameter tuning for differential mining of string patterns. In: ICDM Workshops, pp. 77\u201386. IEEE Computer Society (2008)","DOI":"10.1109\/ICDMW.2008.118"},{"issue":"3","key":"15_CR2","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1007\/s10618-010-0209-3","volume":"23","author":"TD Bie","year":"2011","unstructured":"Bie, T.D.: Maximum entropy models and subjective interestingness: an application to tiles in binary databases. Data Min. Knowl. Discov. 23(3), 407\u2013446 (2011)","journal-title":"Data Min. Knowl. Discov."},{"issue":"1","key":"15_CR3","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1021571501451","volume":"7","author":"JF Boulicaut","year":"2003","unstructured":"Boulicaut, J.F., Bykowski, A., Rigotti, C.: Free-sets: a condensed representation of boolean data for the approximation of frequency queries. Data Min. Knowl. Disc. 7(1), 5\u201322 (2003)","journal-title":"Data Min. Knowl. Disc."},{"key":"15_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/978-3-030-10925-7_23","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"B Cr\u00e9milleux","year":"2019","unstructured":"Cr\u00e9milleux, B., Giacometti, A., Soulet, A.: How your supporters and opponents define your interestingness. In: Berlingerio, M., Bonchi, F., G\u00e4rtner, T., Hurley, N., Ifrim, G. (eds.) ECML PKDD 2018. LNCS (LNAI), vol. 11051, pp. 373\u2013389. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-10925-7_23"},{"key":"15_CR5","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-540-70596-3_18","volume-title":"Conceptual Structures: Knowledge Visualization and Reasoning","author":"F Dau","year":"2008","unstructured":"Dau, F., Ducrou, J., Eklund, P.: Concept similarity and related categories in searchsleuth. In: Eklund, P., Haemmerl\u00e9, O. (eds.) ICCS-ConceptStruct 2008. LNCS (LNAI), vol. 5113, pp. 255\u2013268. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-70596-3_18"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Davey, B.A., Priestley, H.A.: Introduction to Lattices and Order, Second Edition. Cambridge University Press, Cambridge (2002)","DOI":"10.1017\/CBO9780511809088"},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"De Raedt, L., Zimmermann, A.: Constraint-based pattern set mining. In: Proceedings of the Seventh SIAM International Conference on Data Mining. SIAM (2007)","DOI":"10.1137\/1.9781611972771.22"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Dong, G., Li, J.: Efficient mining of emerging patterns: discovering trends and differences. In: Proceedings of the Fifth ACM SIGKDD, pp. 43\u201352 (1999)","DOI":"10.1145\/312129.312191"},{"key":"15_CR9","doi-asserted-by":"crossref","unstructured":"Kane, B., Cuissart, B., Cremilleux, B.: Minimal jumping emerging patterns: computation and practical assessment. In: PAKDD (2015)","DOI":"10.1007\/978-3-319-18038-0_56"},{"issue":"8","key":"15_CR10","doi-asserted-by":"publisher","first-page":"3551","DOI":"10.1021\/acs.jmedchem.7b01890","volume":"61","author":"JP M\u00e9tivier","year":"2018","unstructured":"M\u00e9tivier, J.P., Cuissart, B., Bureau, R., Lepailleur, A.: The pharmacophore network: a computational method for exploring structure-activity relationships from a large chemical data set. J. Med. Chem. 61(8), 3551\u20133564 (2018)","journal-title":"J. Med. Chem."},{"key":"15_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"398","DOI":"10.1007\/3-540-49257-7_25","volume-title":"Database Theory \u2014 ICDT\u201999","author":"N Pasquier","year":"1999","unstructured":"Pasquier, N., Bastide, Y., Taouil, R., Lakhal, L.: Discovering frequent closed itemsets for association rules. In: Beeri, C., Buneman, P. (eds.) ICDT 1999. LNCS, vol. 1540, pp. 398\u2013416. Springer, Heidelberg (1999). https:\/\/doi.org\/10.1007\/3-540-49257-7_25"},{"issue":"11","key":"15_CR12","doi-asserted-by":"publisher","first-page":"14360","DOI":"10.1021\/acsomega.9b02221","volume":"4","author":"D Stumpfe","year":"2019","unstructured":"Stumpfe, D., Hu, H., Bajorath, J.: Evolving concept of activity cliffs. ACS Omega 4(11), 14360\u201314368 (2019)","journal-title":"ACS Omega"},{"issue":"4","key":"15_CR13","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1016\/S0306-4379(03)00072-3","volume":"29","author":"P Tan","year":"2004","unstructured":"Tan, P., Kumar, V., Srivastava, J.: Selecting the right objective measure for association analysis. Inf. Syst. 29(4), 293\u2013313 (2004)","journal-title":"Inf. Syst."},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Van Leeuwen, M., Ukkonen, A.: Fast estimation of the pattern frequency spectrum. In: ECML PKDD 2014, pp. 114\u2013129 (2014)","DOI":"10.1007\/978-3-662-44851-9_8"},{"key":"15_CR15","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/978-3-319-07821-2_5","volume-title":"Frequent Pattern Mining","author":"J Vreeken","year":"2014","unstructured":"Vreeken, J., Tatti, N.: Interesting patterns. In: Aggarwal, C.C., Han, J. (eds.) Frequent Pattern Mining, pp. 105\u2013134. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-07821-2_5"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Webb, G.I.: Self-sufficient itemsets: an approach to screening potentially interesting associations between items. ACM Trans. Knowl. Discov. Data 4(1), 3:1\u20133:20 (2010)","DOI":"10.1145\/1644873.1644876"},{"key":"15_CR17","doi-asserted-by":"crossref","unstructured":"Yan, X., Han, J.: Closegraph: mining closed frequent graph patterns. In: Proceedings of the Ninth ACM SIGKDD, pp. 286\u2013295 (2003)","DOI":"10.1145\/956750.956784"}],"container-title":["Lecture Notes in Computer Science","Advances in Intelligent Data Analysis XX"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-01333-1_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T23:06:05Z","timestamp":1649804765000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-01333-1_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031013324","9783031013331"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-01333-1_15","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":"7 April 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligent Data Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rennes","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","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":"20 April 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 April 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ida2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ida-2022.org\/","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":"75","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":"31","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":"0","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":"41% - 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":"3","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)"}}]}}