{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T09:34:24Z","timestamp":1774949664821,"version":"3.50.1"},"publisher-location":"Berlin, Heidelberg","reference-count":11,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783642346231","type":"print"},{"value":"9783642346248","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"DOI":"10.1007\/978-3-642-34624-8_4","type":"book-chapter","created":{"date-parts":[[2012,11,29]],"date-time":"2012-11-29T11:22:10Z","timestamp":1354188130000},"page":"31-40","source":"Crossref","is-referenced-by-count":27,"title":["Mining Top-K Non-redundant Association Rules"],"prefix":"10.1007","author":[{"given":"Philippe","family":"Fournier-Viger","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent S.","family":"Tseng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"4_CR1","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Imielminski, T., Swami, A.: Mining Association Rules Between Sets of Items in Large Databases. In: Proc. ACM Intern. Conf. on Management of Data, pp. 207\u2013216. ACM Press (June 1993)","DOI":"10.1145\/170036.170072"},{"key":"4_CR2","volume-title":"Data Mining: Concepts and Techniques","author":"J. Han","year":"2006","unstructured":"Han, J., Kamber, M.: Data Mining: Concepts and Techniques, 2nd edn. Morgan Kaufmann Publ., San Francisco (2006)","edition":"2"},{"key":"4_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/978-3-642-30353-1_6","volume-title":"Advances in Artificial Intelligence","author":"P. Fournier-Viger","year":"2012","unstructured":"Fournier-Viger, P., Wu, C.-W., Tseng, V.S.: Mining Top-K Association Rules. In: Kosseim, L., Inkpen, D. (eds.) Canadian AI 2012. LNCS, vol.\u00a07310, pp. 61\u201373. Springer, Heidelberg (2012)"},{"issue":"1","key":"4_CR4","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s10618-005-0255-4","volume":"10","author":"G.I. Webb","year":"2005","unstructured":"Webb, G.I., Zhang, S.: k-Optimal-Rule-Discovery. Data Mining and Knowledge Discovery\u00a010(1), 39\u201379 (2005)","journal-title":"Data Mining and Knowledge Discovery"},{"key":"4_CR5","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1002\/widm.28","volume":"1","author":"G.I. Webb","year":"2011","unstructured":"Webb, G.I.: Filtered top-k association discovery. WIREs Data Mining and Knowledge Discovery\u00a01, 183\u2013192 (2011)","journal-title":"WIREs Data Mining and Knowledge Discovery"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"You, Y., Zhang, J., Yang, Z., Liu, G.: Mining Top-k Fault Tolerant Association Rules by Redundant Pattern Disambiguation in Data Streams. In: Proc. 2010 Intern. Conf. Intelligent Computing and Cognitive Informatics, pp. 470\u2013473. IEEE Press (March 2010)","DOI":"10.1109\/ICICCI.2010.91"},{"key":"4_CR7","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1007\/3-540-44957-4_65","volume-title":"Computational Logic - CL 2000","author":"Y. Bastide","year":"2000","unstructured":"Bastide, Y., Pasquier, N., Taouil, R., Stumme, G., Lakhal, L.: Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets. In: Palamidessi, C., Moniz Pereira, L., Lloyd, J.W., Dahl, V., Furbach, U., Kerber, M., Lau, K.-K., Sagiv, Y., Stuckey, P.J. (eds.) CL 2000. LNCS (LNAI), vol.\u00a01861, pp. 972\u2013986. Springer, Heidelberg (2000)"},{"key":"4_CR8","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/11430919_11","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"G. Gasmi","year":"2005","unstructured":"Gasmi, G., Yahia, S.B., Nguifo, E.M., Slimani, Y.: IGB: A New Informative Generic Base of Association Rules. In: Ho, T.-B., Cheung, D., Liu, H. (eds.) PAKDD 2005. LNCS (LNAI), vol.\u00a03518, pp. 81\u201390. Springer, Heidelberg (2005)"},{"key":"4_CR9","unstructured":"Cherif, C.L., Bellegua, W., Ben Yahia, S., Guesmi, G.: VIE_MGB: A Visual Interactive Exploration of Minimal Generic Basis of Association Rules. In: Proc. of the Intern. Conf. on Concept Lattices and Application (CLA 2005), pp. 179\u2013196 (2005)"},{"key":"4_CR10","unstructured":"Kryszkiewicz, M.: Representative Association Rules and Minimum Condition Maximum Consequence Association Rules"},{"issue":"1","key":"4_CR11","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TKDE.2006.10","volume":"18","author":"C. Lucchese","year":"2006","unstructured":"Lucchese, C., Orlando, S., Perego, R.: Fast and Memory Efficient Mining of Frequent Closed Itemsets. IEEE Trans. Knowl. and Data Eng.\u00a018(1), 21\u201336 (2006)","journal-title":"IEEE Trans. Knowl. and Data Eng."}],"container-title":["Lecture Notes in Computer Science","Foundations of Intelligent Systems"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-34624-8_4.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,4]],"date-time":"2021-05-04T13:01:44Z","timestamp":1620133304000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-34624-8_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"ISBN":["9783642346231","9783642346248"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-34624-8_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012]]}}}