{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T09:38:53Z","timestamp":1742981933382,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319957852"},{"type":"electronic","value":"9783319957869"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-95786-9_4","type":"book-chapter","created":{"date-parts":[[2018,7,3]],"date-time":"2018-07-03T17:55:52Z","timestamp":1530640552000},"page":"44-58","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A New Approach for Mining Representative Patterns"],"prefix":"10.1007","author":[{"given":"Abeda","family":"Sultana","sequence":"first","affiliation":[]},{"given":"Hosneara","family":"Ahmed","sequence":"additional","affiliation":[]},{"given":"Chowdhury Farhan","family":"Ahmed","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,7,4]]},"reference":[{"key":"4_CR1","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1007\/978-3-642-28320-8_11","volume-title":"New Frontiers in Applied Data Mining","author":"K Amphawan","year":"2012","unstructured":"Amphawan, K., Lenca, P., Surarerks, A.: Efficient mining top-k regular-frequent itemset using compressed tidsets. In: Cao, L., Huang, J.Z., Bailey, J., Koh, Y.S., Luo, J. (eds.) PAKDD 2011. LNCS (LNAI), vol. 7104, pp. 124\u2013135. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-28320-8_11"},{"issue":"2","key":"4_CR2","doi-asserted-by":"publisher","first-page":"1924","DOI":"10.1016\/j.eswa.2011.08.055","volume":"39","author":"K Amphawan","year":"2012","unstructured":"Amphawan, K., Lenca, P., Surarerks, A.: Mining top-k regular-frequent itemsets using database partitioning and support estimation. Expert Syst. Appl. 39(2), 1924\u20131936 (2012)","journal-title":"Expert Syst. Appl."},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Bayardo, R.J. : Efficiently mining long patterns from databases. In: Proceeding of the ACM-SIGMOD International Conference on Management of Data, pp. 85\u201393 (1998)","DOI":"10.1145\/276305.276313"},{"issue":"10","key":"4_CR4","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1109\/TKDE.2005.166","volume":"17","author":"G Grahne","year":"2005","unstructured":"Grahne, G., Zhu, J.: Fast algorithms for frequent itemset mining using FP-trees. IEEE Trans. Know. Data Eng. 17(10), 1347\u20131362 (2005)","journal-title":"IEEE Trans. Know. Data Eng."},{"issue":"1","key":"4_CR5","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1023\/B:DAMI.0000005258.31418.83","volume":"8","author":"J Han","year":"2004","unstructured":"Han, J., Pei, J., Yin, J.: Frequent patterns without candidate generation a frequent-pattern tree approach. Data Min. Knowl. Disc. 8(1), 53\u201387 (2004)","journal-title":"Data Min. Knowl. Disc."},{"key":"4_CR6","unstructured":"Han, J., Wang, J., Lu, Y., Tzvetkov, P.: Mining top-k frequent closed pat- terns without minimum support. In: Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM 2002), Maebashi City, Japan, 9\u201312 December, pp. 211\u2013218 (2002)"},{"issue":"3","key":"4_CR7","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.3233\/IFS-141398","volume":"28","author":"G Lee","year":"2014","unstructured":"Lee, G., Yun, U., Ryang, H.: Mining weighted erasable patterns by using underestimated constraint-based pruning technique. J. Intell. Fuzzy Syst. 28(3), 1145\u20131157 (2014)","journal-title":"J. Intell. Fuzzy Syst."},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Leung, C.K.S., Khan, Q.I.: DSTree: a tree structure for the mining of frequent sets from data streams. In: Proceedings of the Sixth International Conference on Data Mining (ICDM 2006), pp. 928\u2013932. IEEE Computer Society, Washington, DC (2006)","DOI":"10.1109\/ICDM.2006.62"},{"key":"4_CR9","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1007\/978-3-319-15702-3_36","volume-title":"Intelligent Information and Database Systems","author":"G Nguyen","year":"2015","unstructured":"Nguyen, G., Le, T., Vo, B., Le, B.: Discovering erasable closed patterns. In: Nguyen, N.T., Trawi\u0144ski, B., Kosala, R. (eds.) ACIIDS 2015. LNCS (LNAI), vol. 9011, pp. 368\u2013376. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-15702-3_36"},{"issue":"1","key":"4_CR10","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/s10489-014-0644-8","volume":"43","author":"G Nguyen","year":"2015","unstructured":"Nguyen, G., Le, T., Vo, B., Le, B.: EIFDD: an efficient approach for erasable itemset mining of very dense datasets. Appl. Intell. 43(1), 85\u201394 (2015)","journal-title":"Appl. Intell."},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Vo, B., Le, T., Nguyen, G., Hong, T.: Efficient algorithms for mining erasable closed patterns from product datasets. In: IEEE Access, p. 1 (2017)","DOI":"10.1109\/ACCESS.2017.2676803"},{"issue":"5","key":"4_CR12","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1109\/TKDE.2005.81","volume":"17","author":"J Wang","year":"2005","unstructured":"Wang, J., Han, J., Lu, Y., Tzvetkov, P.: TFP: an efficient algorithm for mining top-k frequent closed itemsets. IEEE Trans. Knowl. Data Eng. 17(5), 652\u2013664 (2005)","journal-title":"IEEE Trans. Knowl. Data Eng."}],"container-title":["Lecture Notes in Computer Science","Advances in Data Mining. Applications and Theoretical Aspects"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-95786-9_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:23:13Z","timestamp":1710260593000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-95786-9_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319957852","9783319957869"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-95786-9_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"4 July 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICDM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Industrial Conference on Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"New York, NY","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 July 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 July 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"incdm2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.data-mining-forum.de\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"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":"146","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":"24","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":"15","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":"16% - 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":"2","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":"0","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)"}}]}}