{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T18:40:54Z","timestamp":1774291254422,"version":"3.50.1"},"publisher-location":"Berlin, Heidelberg","reference-count":20,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783540654520","type":"print"},{"value":"9783540492573","type":"electronic"}],"license":[{"start":{"date-parts":[[1999,1,1]],"date-time":"1999-01-01T00:00:00Z","timestamp":915148800000},"content-version":"tdm","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":[[1999]]},"DOI":"10.1007\/3-540-49257-7_25","type":"book-chapter","created":{"date-parts":[[2007,11,10]],"date-time":"2007-11-10T02:44:59Z","timestamp":1194662699000},"page":"398-416","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":532,"title":["Discovering Frequent Closed Itemsets for Association Rules"],"prefix":"10.1007","author":[{"given":"Nicolas","family":"Pasquier","sequence":"first","affiliation":[]},{"given":"Yves","family":"Bastide","sequence":"additional","affiliation":[]},{"given":"Rafik","family":"Taouil","sequence":"additional","affiliation":[]},{"given":"Lotfi","family":"Lakhal","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[1999,1,15]]},"reference":[{"key":"25_CR1","doi-asserted-by":"crossref","unstructured":"R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. Proceedings of the ACM SIGMOD Int\u2019l Conference on Management of Data, pages 207\u2013216, May 1993.","DOI":"10.1145\/170036.170072"},{"key":"25_CR2","unstructured":"R. Agrawal and R. Srikant. Fast algorithms for mining association rules. Proceedings of the 20th Int\u2019l Conference on Very Large Data Bases, pages 478\u2013499, June 1994. Expanded version in IBM Research Report RJ9839."},{"key":"25_CR3","doi-asserted-by":"crossref","unstructured":"R. J. Bayardo. Efficiently mining long patterns from databases. Proceedings of the ACM SIGMOD Int\u2019l Conference on Management of Data, pages 85\u201393, June 1998.","DOI":"10.1145\/276305.276313"},{"key":"25_CR4","unstructured":"G. Birkhoff. Lattices theory. In Coll. Pub. XXV, volume 25. American Mathematical Society, 1967. Third edition."},{"key":"25_CR5","doi-asserted-by":"crossref","unstructured":"S. Brin, R. Motwani, J. D. Ullman, and S. Tsur. Dynamic itemset counting and implication rules for market basket data. Proceedings of the ACM SIGMOD Int\u2019l Conference on Management of Data, pages 255\u2013264, May 1997.","DOI":"10.1145\/253262.253325"},{"issue":"6","key":"25_CR6","doi-asserted-by":"publisher","first-page":"866","DOI":"10.1109\/69.553155","volume":"8","author":"M.-S. Chen","year":"1996","unstructured":"M.-S. Chen, J. Han, and P. S. Yu. Data mining: An overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, 8(6):866\u2013883, December 1996.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"25_CR7","unstructured":"B. A. Davey and H. A. Priestley. Introduction to Lattices and Order. Cambridge University Press, 1994. Fourth edition."},{"issue":"95","key":"25_CR8","first-page":"5","volume":"24","author":"V. Duquenne","year":"1986","unstructured":"V. Duquenne and L.-L. Guigues. Famille minimale d\u2019implication informatives r\u00e9sultant d\u2019un tableau de donn\u00e9es binaires. Math. Sci. Hum., 24(95):5\u201318, 1986.","journal-title":"Math. Sci. Hum."},{"key":"25_CR9","doi-asserted-by":"crossref","unstructured":"B. Ganter and K. Reuter. Finding all closed sets: A general approach. In Order, pages 283\u2013290. Kluwer Academic Publishers, 1991.","DOI":"10.1007\/BF00383449"},{"key":"25_CR10","doi-asserted-by":"crossref","unstructured":"D. Lin and Z. M. Kedem. Pincer-search: A new algorithm for discovering the maximum frequent set. Proceedings of the 6th Int\u2019l Conference on Extending Database Technology, pages 105\u2013119, March 1998.","DOI":"10.1007\/BFb0100980"},{"issue":"113","key":"25_CR11","first-page":"35","volume":"29","author":"M. Luxenburger","year":"1991","unstructured":"M. Luxenburger. Implications partielles dans un contexte. Math. Inf. Sci. Hum., 29(113):35\u201355, 1991.","journal-title":"Math. Inf. Sci. Hum."},{"issue":"3","key":"25_CR12","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1023\/A:1009796218281","volume":"1","author":"H. Mannila","year":"1997","unstructured":"H. Mannila and H. Toivonen. Levelwise search and borders of theories in knowledge discovery. Data Mining and Knowledge Discovery, 1(3):241\u2013258, 1997.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"25_CR13","unstructured":"H. Mannila, H. Toivonen, and A. I. Verkamo. Efficient algorithms for discovering association rules. Proceedings of the AAAI Workshop on Knowledge Discovery in Databases, pages 181\u2013192, July 1994."},{"key":"25_CR14","unstructured":"A. M. Mueller. Fast sequential and parallel algorithms for association rules mining: A comparison. Technical report, Faculty of the Graduate School of The University of Maryland, 1995."},{"key":"25_CR15","unstructured":"N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Pruning closed itemset lattices for association rules. Proceedings of the BDA French Conference on Advanced Databases, October 1998. To appear."},{"key":"25_CR16","unstructured":"A. Savasere, E. Omiecinski, and S. Navathe. An efficient algorithm for mining association rules in larges databases. Proceedings of the 21th Int\u2019l Conference on Very Large Data Bases, pages 432\u2013444, September 1995."},{"key":"25_CR17","unstructured":"H. Toivonen. Sampling large databases for association rules. Proceedings of the 22nd Int\u2019l Conference on Very Large Data Bases, pages 134\u2013145, September 1996."},{"key":"25_CR18","unstructured":"H. Toivonen, M. Klemettinen, P. Ronkainen, K. Hatonen, and H. Mannila. Pruning and grouping discovered association rules. ECML-95 Workshop on Statistics, Machine Learning, and Knowledge Discovery in Databases, pages 47\u201352, April 1995."},{"key":"25_CR19","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1016\/0898-1221(92)90120-7","volume":"23","author":"R. Wille","year":"1992","unstructured":"R. Wille. Concept lattices and conceptual knowledge systems. Computers and Mathematics with Applications, 23:493\u2013515, 1992.","journal-title":"Computers and Mathematics with Applications"},{"key":"25_CR20","doi-asserted-by":"crossref","unstructured":"M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New algorithms for fast discovery of association rules. Proceedings of the 3rd Int\u2019l Conference on Knowledge Discovery in Databases, pages 283\u2013286, August 1997.","DOI":"10.1007\/978-1-4615-5669-5_1"}],"container-title":["Lecture Notes in Computer Science","Database Theory \u2014 ICDT\u201999"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/3-540-49257-7_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,19]],"date-time":"2019-05-19T15:04:07Z","timestamp":1558278247000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/3-540-49257-7_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1999]]},"ISBN":["9783540654520","9783540492573"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/3-540-49257-7_25","relation":{},"ISSN":["0302-9743"],"issn-type":[{"value":"0302-9743","type":"print"}],"subject":[],"published":{"date-parts":[[1999]]},"assertion":[{"value":"15 January 1999","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}