{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T14:17:22Z","timestamp":1725891442305},"publisher-location":"Berlin, Heidelberg","reference-count":15,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642309465"},{"type":"electronic","value":"9783642309472"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"DOI":"10.1007\/978-3-642-30947-2_13","type":"book-chapter","created":{"date-parts":[[2012,6,18]],"date-time":"2012-06-18T05:16:30Z","timestamp":1339996590000},"page":"94-103","source":"Crossref","is-referenced-by-count":1,"title":["Integrating Quantitative Attributes in Hierarchical Clustering of Transactional Data"],"prefix":"10.1007","author":[{"given":"Mihaela","family":"Vrani\u0107","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Damir","family":"Pintar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zoran","family":"Sko\u010dir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"13_CR1","unstructured":"Han, J., Kamber, M.: Data mining: concepts and techniques. The Morgan Kaufmann series in data management systems. Elsevier (2006)"},{"key":"13_CR2","doi-asserted-by":"crossref","unstructured":"Agrawal, R., Imieli\u0144ski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, SIGMOD 1993, New York, pp. 207\u2013216 (1993)","DOI":"10.1145\/170036.170072"},{"issue":"8","key":"13_CR3","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1080\/0266476042000270563","volume":"31","author":"B. Padmanabhan","year":"2004","unstructured":"Padmanabhan, B.: The interestingness paradox in pattern discovery. Journal of Applied Statistics\u00a031(8), 1019\u20131035 (2004)","journal-title":"Journal of Applied Statistics"},{"key":"13_CR4","unstructured":"Piatetsky-Shapiro, G.: Discovery, analysis and presentation of strong rules. In: Knowledge Discovery in Databases, pp. 229\u2013248. AAAI Press (1991)"},{"key":"13_CR5","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1016\/S0306-4379(03)00072-3","volume":"29","author":"P.N. Tan","year":"2004","unstructured":"Tan, P.N., Kumar, V., Srivastava, J.: Selecting the right objective measure for association analysis. Information Systems\u00a029, 293\u2013313 (2004)","journal-title":"Information Systems"},{"key":"13_CR6","doi-asserted-by":"crossref","unstructured":"Webb, G.I.: Discovering significant rules. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006, New York, pp. 434\u2013443 (2006)","DOI":"10.1145\/1150402.1150451"},{"key":"13_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1644873.1644876","volume":"4","author":"G.I. Webb","year":"2010","unstructured":"Webb, G.I.: Self-sufficient itemsets: An approach to screening potentially interesting associations between items. ACM Transactions on Knowledge Discovery From Data\u00a04, 1\u201320 (2010)","journal-title":"ACM Transactions on Knowledge Discovery From Data"},{"issue":"4","key":"13_CR8","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1080\/00051144.2011.11828434","volume":"52","author":"S. Pinju\u0161i\u0107","year":"2011","unstructured":"Pinju\u0161i\u0107, S., Vrani\u0107, M., Pintar, D.: Improvement of hierarchical clustering results by refinement of variable types and distance measures. Automatika: Journal for Control, Measurement, Electronics, Computing and Communications\u00a052(4), 353\u2013364 (2011)","journal-title":"Automatika: Journal for Control, Measurement, Electronics, Computing and Communications"},{"key":"13_CR9","unstructured":"Vrani\u0107, M.: Designing concise representation of correlations among elements in transactional data. PhD thesis, FER, Zagreb, Croatia (2011)"},{"key":"13_CR10","unstructured":"Vrani\u0107, M., Pintar, D., Gamberger, D.: Adapting hierarchical clustering distance measures for improved presentation of relationships between transaction elements. Journal of Information and Organizational Sciences 36(1) (in press, 2012)"},{"key":"13_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/235968.233311","volume":"25","author":"R. Srikant","year":"1996","unstructured":"Srikant, R., Agrawal, R.: Mining quantitative association rules in large relational tables. SIGMOD Rec.\u00a025, 1\u201312 (1996)","journal-title":"SIGMOD Rec."},{"key":"13_CR12","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1109\/ICDM.2004.10038","volume-title":"Proceedings of the Fourth IEEE International Conference on Data Mining, ICDM 2004","author":"U. Ruckert","year":"2004","unstructured":"Ruckert, U., Richter, L., Kramer, S.: Quantitative association rules based on half-spaces: An optimization approach. In: Proceedings of the Fourth IEEE International Conference on Data Mining, ICDM 2004, pp. 507\u2013510. IEEE Computer Society, Washington DC (2004)"},{"key":"13_CR13","doi-asserted-by":"crossref","unstructured":"Aumann, Y., Lindel, Y.: A statistical theory for quantitative association rules. Journal of Intelligent Information Systems, 261\u2013270 (1999)","DOI":"10.1145\/312129.312243"},{"key":"13_CR14","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1007\/978-3-540-30116-5_58","volume-title":"Knowledge Discovery in Databases: PKDD 2004","author":"J. Dem\u0161ar","year":"2004","unstructured":"Dem\u0161ar, J., Zupan, B., Leban, G., Curk, T.: Orange: From Experimental Machine Learning to Interactive Data Mining. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) PKDD 2004. LNCS (LNAI), vol.\u00a03202, pp. 537\u2013539. Springer, Heidelberg (2004)"},{"key":"13_CR15","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/ICCGI.2010.28","volume-title":"Proceedings of the 2010 Fifth International Multi-conference on Computing in the Global Information Technology, ICCGI 2010","author":"M. Vrani\u0107","year":"2010","unstructured":"Vrani\u0107, M., Pintar, D., Sko\u010dir, Z.: Generation and analysis of tree structures based on association rules and hierarchical clustering. In: Proceedings of the 2010 Fifth International Multi-conference on Computing in the Global Information Technology, ICCGI 2010, pp. 48\u201353. IEEE Computer Society, Washington DC (2010)"}],"container-title":["Lecture Notes in Computer Science","Agent and Multi-Agent Systems. Technologies and Applications"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-30947-2_13.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,4]],"date-time":"2021-05-04T07:34:00Z","timestamp":1620113640000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-30947-2_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"ISBN":["9783642309465","9783642309472"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-30947-2_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2012]]}}}