{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T06:00:47Z","timestamp":1725516047861},"publisher-location":"Berlin, Heidelberg","reference-count":26,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540710790"},{"type":"electronic","value":"9783540710806"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/978-3-540-71080-6_4","type":"book-chapter","created":{"date-parts":[[2008,7,22]],"date-time":"2008-07-22T12:02:13Z","timestamp":1216728133000},"page":"46-59","source":"Crossref","is-referenced-by-count":1,"title":["A Methodology for Exploring Association Models"],"prefix":"10.1007","author":[{"given":"Alipio","family":"Jorge","sequence":"first","affiliation":[]},{"given":"Jo\u00e3o","family":"Po\u00e7as","sequence":"additional","affiliation":[]},{"given":"Paulo J.","family":"Azevedo","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"4_CR1","unstructured":"Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast Discovery of Association Rules. Advances in Knowledge Discovery and Data Mining, 307\u2013328 (1996)"},{"key":"4_CR2","unstructured":"Azevedo, P.J.: CAREN \u2013 A Java based Apriori Implementation for Classification Purposes, Technical Report, Departamento de Inform\u00e1tica, Universidade do Minho, http:\/\/www.di.uminho.pt\/~pja\/class\/caren.html"},{"key":"4_CR3","volume-title":"Data Mining Techniques: For Marketing, Sales, and Customer Support","author":"M.J.A. Berry","year":"1997","unstructured":"Berry, M.J.A., Linoff, G.S.: Data Mining Techniques: For Marketing, Sales, and Customer Support. John Wiley & Sons, Chichester (1997)"},{"issue":"1","key":"4_CR4","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1023\/B:DAMI.0000005256.79013.69","volume":"8","author":"T. Brijs","year":"2004","unstructured":"Brijs, T., Swinnen, G., Vanhoof, K., Wets, G.: Building an Association Rules Framework to Improve Product Assortment Decisions. Data Min. Knowl. Discov.\u00a08(1), 7\u201323 (2004)","journal-title":"Data Min. Knowl. Discov."},{"issue":"2","key":"4_CR5","first-page":"255","volume":"26","author":"S. Brin","year":"1997","unstructured":"Brin, S., Motwani, R., Ullman, J.D., Tsur, S.: Dynamic itemset counting and implication rules for market basket data. SIGMOD Record (ACM Special Interest Group on Man-agement of Data)\u00a026(2), 255 (1997), http:\/\/citeseer.nj.nec.com\/brin97dynamic.html","journal-title":"SIGMOD Record (ACM Special Interest Group on Man-agement of Data)"},{"key":"4_CR6","volume-title":"Expert Systems with Applications","author":"M.-C. Chen","year":"2006","unstructured":"Chen, M.-C., Lin, C.-P.: A data mining approach to product assortment and shelf space allocation. In: Expert Systems with Applications. Elsevier, Amsterdam (2006)"},{"key":"4_CR7","volume-title":"Expert Systems with Applications","author":"H.-J. Chang","year":"2007","unstructured":"Chang, H.-J., Hung, L.-P., Ho, C.-L.: An anticipation model of potential customers\u2019 pur-chasing behavior based on clustering analysis and association rules analysis. In: Expert Systems with Applications. Elsevier, Amsterdam (2007)"},{"key":"4_CR8","unstructured":"Clementine Software, SPSS, http:\/\/www.spss.com"},{"key":"4_CR9","unstructured":"Data Mining Group (PMML development), http:\/\/www.dmg.org\/"},{"issue":"2","key":"4_CR10","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1023\/B:DAMI.0000031629.31935.ac","volume":"9","author":"A. Demiriz","year":"2004","unstructured":"Demiriz, A.: Enhancing Product Recommender Systems on Sparse Binary Data. Data Min. Knowl. Discov.\u00a09(2), 147\u2013170 (2004)","journal-title":"Data Min. Knowl. Discov."},{"key":"4_CR11","first-page":"178","volume-title":"Proceedings of the Fourth SIAM International Conference on Data Mining","author":"A. Jorge","year":"2004","unstructured":"Jorge, A.: Hierarchical Clustering for thematic browsing and summarization of large sets of Association Rules. In: Proceedings of the Fourth SIAM International Conference on Data Mining, pp. 178\u2013187. SIAM press, Philadelphia (2004)"},{"key":"4_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1007\/3-540-36182-0_43","volume-title":"Discovery Science","author":"A. Jorge","year":"2002","unstructured":"Jorge, A., Po\u00e7as, J., Azevedo, P.: Post-processing operators for browsing large sets of association rules. In: Lange, S., Satoh, K., Smith, C.H. (eds.) DS 2002. LNCS, vol.\u00a02534, pp. 414\u2013421. Springer, Heidelberg (2002)"},{"key":"4_CR13","volume-title":"Proc. of the Thirteenth International Conference on Data Engineering, ICDE 1997","author":"B. Lent","year":"1997","unstructured":"Lent, B., Swami, A., Widom, J.: Clustering Association Rules. In: Gray, A., Larson, P. (eds.) Proc. of the Thirteenth International Conference on Data Engineering, ICDE 1997, IEEE Computer Society, Birmingham (1997)"},{"key":"4_CR14","volume-title":"Proceedings of KDD 2001","author":"E. Kandogan","year":"2001","unstructured":"Kandogan, E.: Visualizing Multi-dimensional Clusters, Trends and Outliers using Star Coordinates. In: Proceedings of KDD 2001, ACM Press, New York (2001)"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Klemettinen, M., Mannila, H., Ronkainen, P., Toivonen, H., Verkamo, A.: Finding interesting rules from large sets of discovered association rules. In: Nabil, R., et al. (eds.) Proceedings of 3rd International Conference on Information and Knowledge Management, pp. 401\u2013407. ACM Press (1994)","DOI":"10.1145\/191246.191314"},{"key":"4_CR16","unstructured":"Li, W., Han, J., Pei, J.: CMAR: Accurate and Efficient Classification Based on Multiple-Class-Association Rules. In: IEEE International Conference on Data Mining (2001), http:\/\/citeseer.nj.nec.com\/li01cmar.html"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Ma, Y., Liu, B., Wong, K.: Web for Data Mininig: Organizing and Inter-preting the Discovered Rules Using the Web, School. SIGKDD Explorations, ACM SIGKDD\u00a02(1) (July 2000)","DOI":"10.1145\/360402.360408"},{"key":"4_CR18","unstructured":"Microsoft Web Site (JScript and JavaScript) and ASP, http:\/\/support.microsoft.com , http:\/\/support.microsoft.com"},{"key":"4_CR19","unstructured":"Po\u00e7as, J.: Um ambiente de p\u00f3s-processamento para regras de associa\u00e7\u00e3o. MSc. Thesis in Portuguese, Mestrado em An\u00e1lise de Dados e Sistemas de Apoio \u00e0 Decis\u00e3o (2003)"},{"key":"4_CR20","unstructured":"Savasere, A., Omiecinski, E., Navathe, S.: An efficient algorithm for mining association rules in large databases. In: Proc. of 21st Intl. Conf. on Very Large Databases (VLDB) (1995)"},{"key":"4_CR21","unstructured":"Silberschatz, A., Tuzhilin, A.: On subjective measures of interestingness in knowledge discovery. In: Proceedings of the First International Conference on Knowledge Discovery and Data Mining, pp. 275\u2013281 (1995), http:\/\/citeseer.nj.nec.com\/silberschatz95subjective.html"},{"key":"4_CR22","unstructured":"Tan, P.-N., Kumar, V.: Interestingness measures for association patterns: a perspective. In: Proceedings of the Workshop on Post-processing in Machine Learning and Data Mining, associated to KDD 2000 (2000)"},{"key":"4_CR23","unstructured":"Toivonen, H.: Sampling large databases for association rules. In: Proc. of 22nd Intl. Conf. on Very Large Databases (VLDB) (1996), http:\/\/citeseer.nj.nec.com\/toivonen96sampling.html"},{"key":"4_CR24","unstructured":"W3C DOM Level 1 specification, http:\/\/www.w3.org\/DOM\/"},{"key":"4_CR25","unstructured":"W3C, Scalable Vector Graphics (SVG) 1.0 Specification, W3C Recommendation (September 2001), http:\/\/www.w3.org\/TR\/SVG\/"},{"key":"4_CR26","unstructured":"Wettshereck, D.: A KDDSE-independent PMML Visualizer. In: Bohanec, M., Mladenic, D., Lavrac, N. (eds.) Proc. of IDDM 2002, workshop on Integration aspects of Decision Support and Data Mining. associated to the conferences ECML\/PKDD (2002)"}],"container-title":["Lecture Notes in Computer Science","Visual Data Mining"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-71080-6_4.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,3]],"date-time":"2021-05-03T04:36:55Z","timestamp":1620016615000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-71080-6_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9783540710790","9783540710806"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-71080-6_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[]}}