{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:43:17Z","timestamp":1781109797104,"version":"3.54.1"},"reference-count":0,"publisher":"IGI Global Scientific Publishing","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,1,1]]},"abstract":"<p>Existing algorithms for high-utility itemsets mining are column enumeration based, adopting an Apriorilike candidate set generation-and-test approach, and thus are inadequate in datasets with high dimensions or long patterns. To solve the problem, this paper proposed a hybrid model and a row enumeration-based algorithm, i.e., Inter-transaction, to discover high-utility itemsets from two directions: an existing algorithm can be used to seek short high-utility itemsets from the bottom, while Inter-transaction can be used to seek long high-utility itemsets from the top. Inter-transaction makes full use of the characteristic that there are few common items between or among long transactions. By intersecting relevant transactions, the new algorithm can identify long high-utility itemsets, without extending short itemsets step by step. In addition, we also developed new pruning strategies and an optimization technique to improve the performance of Inter-transaction.<\/p>","DOI":"10.4018\/jdwm.2009010104","type":"journal-article","created":{"date-parts":[[2011,2,15]],"date-time":"2011-02-15T13:41:11Z","timestamp":1297777271000},"page":"57-73","source":"Crossref","is-referenced-by-count":10,"title":["A Hybrid Method for High-Utility Itemsets Mining in Large High-Dimensional Data"],"prefix":"10.4018","volume":"5","author":[{"given":"Guangzhu","family":"Guangzhu Yu","sequence":"first","affiliation":[{"name":"Donghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shihuang","family":"Shao","sequence":"additional","affiliation":[{"name":"Donghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Luo","sequence":"additional","affiliation":[{"name":"Guangdong University of Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianhui","family":"Zeng","sequence":"additional","affiliation":[{"name":"Donghua University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","container-title":["International Journal of Data Warehousing and Mining"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=1823","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T16:47:31Z","timestamp":1654102051000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jdwm.2009010104"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2009,1,1]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2009,1]]}},"URL":"https:\/\/doi.org\/10.4018\/jdwm.2009010104","relation":{},"ISSN":["1548-3924","1548-3932"],"issn-type":[{"value":"1548-3924","type":"print"},{"value":"1548-3932","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,1,1]]}}}