{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T22:43:37Z","timestamp":1778539417299,"version":"3.51.4"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,8,22]],"date-time":"2013-08-22T00:00:00Z","timestamp":1377129600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2014,1]]},"DOI":"10.1007\/s10115-012-0492-y","type":"journal-article","created":{"date-parts":[[2013,8,21]],"date-time":"2013-08-21T05:08:52Z","timestamp":1377061732000},"page":"85-107","source":"Crossref","is-referenced-by-count":120,"title":["An efficient projection-based indexing approach for mining high utility itemsets"],"prefix":"10.1007","volume":"38","author":[{"given":"Guo-Cheng","family":"Lan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tzung-Pei","family":"Hong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent S.","family":"Tseng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,8,22]]},"reference":[{"key":"492_CR1","unstructured":"Agrawal R, Srikant R (1994) Fast algorithm for mining association rules. In: Proceeding of the international conference on very large data bases, pp 487\u2013499"},{"key":"492_CR2","unstructured":"Agrawal R, Srikant R, Vu Q (1997) Mining association rules with item constraints. In: Proceeding of the 3rd international conference on knowledge discovery in databases and data mining, pp 66\u201373"},{"key":"492_CR3","doi-asserted-by":"crossref","unstructured":"Agrawal R, Imielinksi T, Swami A (1993) Mining association rules between sets of items in large database. In: Proceeding of the ACM SIGMOD international conference on management of data, pp 207\u2013216","DOI":"10.1145\/170036.170072"},{"issue":"1","key":"492_CR4","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s10115-009-0205-3","volume":"23","author":"LM Aouad","year":"2010","unstructured":"Aouad LM, Le-Khac NA, Kechadi MT (2010) Performance study of distributed a priori-like frequent itemsets mining. Knowl Inf Syst 23(1): 55\u201372","journal-title":"Knowl Inf Syst"},{"issue":"1","key":"492_CR5","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s10115-009-0212-4","volume":"21","author":"M Boley","year":"2009","unstructured":"Boley M, Grosskreutz H (2009) Approximating the number of frequent sets in dense data. Knowl Inf Syst 21(1): 65\u201389","journal-title":"Knowl Inf Syst"},{"key":"492_CR6","doi-asserted-by":"crossref","unstructured":"Bonchi F, Lucchese C (2005) Pushing tougher constraints in frequent pattern mining. In: Proceeding of the Pacific-Asia conference on knowledge discovery and data mining, pp 114\u2013124","DOI":"10.1007\/11430919_15"},{"key":"492_CR7","doi-asserted-by":"crossref","unstructured":"Bonchi F, Giannotti F, Mazzanti A, Pedreschi D (2003) ExAMiner: optimized level-wise frequent pattern mining with monotone constraints. In: Proceeding of the 3rd IEEE international conference on data mining, pp 11\u201318","DOI":"10.1109\/ICDM.2003.1250892"},{"key":"492_CR8","unstructured":"Boulicaut JF, Jeudy B (2000) Using constraints during itemset mining: should we prune or not? In: Proceeding of the Bases de Donn\u00e9es Avanc\u00e9es BDA\u201900, pp 221\u2013237"},{"key":"492_CR9","doi-asserted-by":"crossref","unstructured":"Chan R, Yang Q, Shen Y (2003) Mining high utility itemsets. In: Proceeding of the 3rd IEEE international conference on data mining, pp 19\u201326","DOI":"10.1109\/ICDM.2003.1250893"},{"issue":"8","key":"492_CR10","first-page":"2775","volume":"4","author":"CJ Chu","year":"2008","unstructured":"Chu CJ, Tseng V, Liang T (2008) Mining temporal rare utility itemsets in large databases using relative utility thresholds. Int J Innov Comput Inf Control 4(8): 2775\u20132792","journal-title":"Int J Innov Comput Inf Control"},{"key":"492_CR11","unstructured":"Erwin A, Gopalan RP, Achuthan NR (2007) A bottom-up projection based algorithm for mining high utility itemsets. In: Proceeding of the 2nd workshop on integrating AI and data mining, pp 3\u201311"},{"key":"492_CR12","doi-asserted-by":"crossref","unstructured":"Erwin A, Gopalan RP, Achuthan NR (2007) CTU-Mine\u2014an efficient high utility itemset mining algorithm using the pattern growth approach. In: Proceeding of the 7th IEEE international conferences on computer and information technology, pp 71\u201376","DOI":"10.1109\/CIT.2007.120"},{"key":"492_CR13","unstructured":"Frequent Itemsets Mining Dataset Repository. Available at ( http:\/\/fimi.cs.helsinki.fi\/data\/ )"},{"key":"492_CR14","doi-asserted-by":"crossref","unstructured":"Han J, Pei J, Yin Y (2000) Mining frequent patterns without candidate generation. In: Proceeding of the ACM SIGMOD international conference on management of data, pp 1\u201312","DOI":"10.1145\/342009.335372"},{"issue":"8","key":"492_CR15","first-page":"46","volume":"32","author":"J Han","year":"1999","unstructured":"Han J, Lakshmanan VS, Ng RT (1999) Constraint-based, multidimensional data mining. In: IEEE Comput 32(8): 46\u201350","journal-title":"In: IEEE Comput"},{"issue":"11","key":"492_CR16","doi-asserted-by":"crossref","first-page":"3317","DOI":"10.1016\/j.patcog.2007.02.003","volume":"40","author":"J Hu","year":"2007","unstructured":"Hu J, Mojsilovic A (2007) High-utility pattern mining: a method for discovery of high-utility item sets. Pattern Recogn 40(11): 3317\u20133324","journal-title":"Pattern Recogn"},{"key":"492_CR17","unstructured":"IBM Quest Data Mining Project, Quest Synthetic Data Generation Code. Available at ( http:\/\/www.almaden.ibm.com\/cs\/quest\/syndata.html )"},{"key":"492_CR18","doi-asserted-by":"crossref","unstructured":"Li HF, Huang HY, Lee SY (2010) Fast and Memory efficient mining of high utility itemsets from data streams: with and without negative item profits. Knowl Inf Syst. On-line First, doi: 10.1007\/s10115-010-0330-z","DOI":"10.1007\/s10115-010-0330-z"},{"issue":"5","key":"492_CR19","doi-asserted-by":"crossref","first-page":"5851","DOI":"10.1016\/j.eswa.2010.11.040","volume":"38","author":"GC Lan","year":"2011","unstructured":"Lan GC, Hong TP, Tseng VS (2011) Discovery of high utility itemsets from on-shelf time periods of products. Exp Syst Appl 38(5): 5851\u20135857","journal-title":"Exp Syst Appl"},{"issue":"1","key":"492_CR20","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.datak.2007.06.009","volume":"64","author":"YC Li","year":"2008","unstructured":"Li YC, Yeh JS, Chang CC (2008) Isolated items discarding strategy for discovering high utility itemsets. Data Knowl Eng 64(1): 198\u2013217","journal-title":"Data Knowl Eng"},{"key":"492_CR21","unstructured":"Lin D-I, Kedem ZM (1998) Pincer-search: a new algorithm for discovering the maximum frequent set. In: Proceeding of the 6th international conference on extending database technology, pp 103\u2013119"},{"key":"492_CR22","doi-asserted-by":"crossref","unstructured":"Liu J, Pan Y, Wang K, Han J, (2002) Mining frequent item sets by opportunistic projection. In: Proceeding of the international conference on knowledge discovery in databases, pp 229\u2013238","DOI":"10.1145\/775047.775081"},{"key":"492_CR23","doi-asserted-by":"crossref","unstructured":"Liu Y, Liao W, Choudhary A (2005) A fast high utility itemsets mining algorithm. In: Proceeding of the utility-based data mining workshop, pp 90\u201399","DOI":"10.1145\/1089827.1089839"},{"key":"492_CR24","unstructured":"Ng RT, Lakshmanan VS, Han J, Pang A (1998) Exploratory mining and pruning optimizations of constrained association rules. In: Proceeding of the ACM SIGMOD international conference on management of data, pp 13\u201324"},{"key":"492_CR25","unstructured":"Pei J, Han J, Lakshmanan VS (2001) Mining frequent item sets with convertible constraints. In: Proceeding of the 17th international conference on data engineering, pp 433\u2013442"},{"issue":"11","key":"492_CR26","first-page":"1424","volume":"16","author":"J Pei","year":"2004","unstructured":"Pei J, Han J, Mortazavi-Asl B, Wang J, Pinto H, Chen Q, Dayal U, Hsu M (2004) Mining sequential patterns by pattern-growth: the PrefixSpan approach. In: IEEE Trans Knowl Data Eng 16(11): 1424\u20131440","journal-title":"In: IEEE Trans Knowl Data Eng"},{"key":"492_CR27","unstructured":"Srikant R, Agrawal R (1995) Mining generalized association rules. In: Proceeding of the 21st international conference on very large data bases, pp 407\u2013419"},{"key":"492_CR28","unstructured":"Tseng VS, Chu CJ, Liang T (2006) Efficient mining of temporal high utility itemsets from data streams. In: Proceeding of the ACM KDD workshop on utility-based data mining, pp 1105\u20131117"},{"issue":"3","key":"492_CR29","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.datak.2005.10.004","volume":"59","author":"H Yao","year":"2006","unstructured":"Yao H, Hamilton HJ (2006) Mining itemset utilities from transaction databases. Data Knowl Eng 59(3): 603\u2013626","journal-title":"Data Knowl Eng"},{"key":"492_CR30","doi-asserted-by":"crossref","unstructured":"Yeh JS, Chang CY, Wang YT (2008) Efficient algorithms for incremental utility mining. In: Proceeding of the international conference on ubiquitous information management and communication, pp 229\u2013234","DOI":"10.1145\/1352793.1352839"},{"key":"492_CR31","unstructured":"Yu G, Li K, Shao S (2008) Mining high utility itemsets in large high dimensional data. In: Proceeding of the international workshop on knowledge discovery and data mining, pp 17\u201320"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-012-0492-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-012-0492-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-012-0492-y","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,21]],"date-time":"2019-07-21T14:47:35Z","timestamp":1563720455000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-012-0492-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,8,22]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,1]]}},"alternative-id":["492"],"URL":"https:\/\/doi.org\/10.1007\/s10115-012-0492-y","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,8,22]]}}}