{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:27:33Z","timestamp":1753882053128,"version":"3.41.2"},"reference-count":28,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Info. Know. Mgmt."],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:p> We tackle the problem of discriminative itemset mining. Given a set of datasets, we want to find the itemsets that are frequent in the target dataset and have much higher frequencies compared with the same itemsets in other datasets. Such itemsets are very useful for dataset discrimination. We demonstrate that this problem has important applications and, at a same time, is very challenging. We present the DISSparse algorithm, a mining method that uses two determinative heuristics based on the sparsity characteristics of the discriminative itemsets as a small subset of the frequent itemsets. We prove that the DISSparse algorithm is sound and complete. We experimentally investigate the performance of the proposed DISSparse on a range of datasets, evaluating its efficiency and stability and demonstrating it is substantially faster than the baseline method. <\/jats:p>","DOI":"10.1142\/s0219649222500095","type":"journal-article","created":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T15:57:21Z","timestamp":1638547041000},"source":"Crossref","is-referenced-by-count":4,"title":["<i>DISSparse<\/i>: Efficient Mining of Discriminative Itemsets"],"prefix":"10.1142","volume":"21","author":[{"given":"Majid","family":"Seyfi","sequence":"first","affiliation":[{"name":"Data Science Discipline, Science and Engineering faculty, Queensland University of Technology, Brisbane, Queensland 4000, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richi","family":"Nayak","sequence":"additional","affiliation":[{"name":"Data Science Discipline, Science and Engineering faculty, Queensland University of Technology, Brisbane, Queensland 4000, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Xu","sequence":"additional","affiliation":[{"name":"Data Science Discipline, Science and Engineering faculty, Queensland University of Technology, Brisbane, Queensland 4000, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shlomo","family":"Geva","sequence":"additional","affiliation":[{"name":"Data Science Discipline, Science and Engineering faculty, Queensland University of Technology, Brisbane, Queensland 4000, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,12,3]]},"reference":[{"key":"S0219649222500095BIB001","first-page":"487","volume-title":"Proceedings of the 20th International Conference on Very Large Data Bases VLDB","volume":"1215","author":"Agrawal R","year":"1994"},{"key":"S0219649222500095BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/WI.2005.96"},{"key":"S0219649222500095BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipl.2009.10.012"},{"key":"S0219649222500095BIB004","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45681-3_4"},{"key":"S0219649222500095BIB005","doi-asserted-by":"publisher","DOI":"10.1023\/A:1011429418057"},{"key":"S0219649222500095BIB006","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2007.367917"},{"key":"S0219649222500095BIB007","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497425"},{"key":"S0219649222500095BIB008","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-021-05844-9"},{"key":"S0219649222500095BIB009","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.03.004"},{"key":"S0219649222500095BIB010","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-012-4638-z"},{"volume-title":"Contrast Data Mining: Concepts, Algorithms, and Applications","year":"2012","author":"Dong G","key":"S0219649222500095BIB011"},{"key":"S0219649222500095BIB012","doi-asserted-by":"publisher","DOI":"10.1145\/312129.312191"},{"key":"S0219649222500095BIB013","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-47887-6_45"},{"key":"S0219649222500095BIB014","series-title":"Proceedings","first-page":"36","volume-title":"European Conference, ECML PKDD 2016","author":"Fournier-Viger P","year":"2016"},{"key":"S0219649222500095BIB016","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.09.047"},{"key":"S0219649222500095BIB017","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.11.043"},{"key":"S0219649222500095BIB018","first-page":"2070","volume-title":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","author":"Leonardo P","year":"2018"},{"key":"S0219649222500095BIB019","doi-asserted-by":"publisher","DOI":"10.1145\/1281192.1281240"},{"key":"S0219649222500095BIB020","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-010-0094-0"},{"key":"S0219649222500095BIB021","first-page":"377","volume":"10","author":"Novak PK","year":"2009","journal-title":"Journal of Machine Learning Research"},{"volume-title":"C4.5: Programs for Machine Learning","year":"2014","author":"Quinlan JR","key":"S0219649222500095BIB022"},{"key":"S0219649222500095BIB023","doi-asserted-by":"publisher","DOI":"10.1109\/IWACI.2011.6159996"},{"key":"S0219649222500095BIB025","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-11749-2_10"},{"key":"S0219649222500095BIB026","doi-asserted-by":"publisher","DOI":"10.1145\/3106426.3106429"},{"key":"S0219649222500095BIB027","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-021-01550-y"},{"key":"S0219649222500095BIB028","doi-asserted-by":"publisher","DOI":"10.1145\/2700409"},{"key":"S0219649222500095BIB029","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2012.218"},{"key":"S0219649222500095BIB030","doi-asserted-by":"publisher","DOI":"10.1145\/347090.347158"}],"container-title":["Journal of Information &amp; 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