Finding localized associations in market basket data, IEEE Transactions on Knowledge and Data Engineering, vol.14, issue.1, pp.51-62, 2002. ,
DOI : 10.1109/69.979972
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.1683
Customer-oriented catalog segmentation: Effective solution approaches, Decision Support Systems, vol.42, issue.3, pp.1860-1871, 2006. ,
DOI : 10.1016/j.dss.2006.04.010
Context-Based Similarity Measures for Categorical Databases, The 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp.201-210, 2000. ,
DOI : 10.1007/3-540-45372-5_20
Dictionary of Distances, 2006. ,
Distance measures for point sets and their computation, Acta Informatica, vol.34, issue.2, pp.109-133, 1997. ,
DOI : 10.1007/s002360050075
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.42.5823
A microeconomic data mining problem, Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '04, pp.557-562, 2004. ,
DOI : 10.1145/1014052.1014119
Segmenting customers by transaction data with concept hierarchy, Expert Systems with Applications, vol.39, issue.6, pp.6221-6228, 2012. ,
DOI : 10.1016/j.eswa.2011.12.005
Customer segmentation and strategy development based on customer lifetime value: A case study, Expert Systems with Applications, vol.31, issue.1, pp.101-107, 2006. ,
DOI : 10.1016/j.eswa.2005.09.004
A Microeconomic View of Data Mining, Data Mining and Knowledge Discovery, vol.2, issue.4, pp.311-324, 1998. ,
DOI : 10.1023/A:1009726428407
Application of data mining techniques in customer relationship management: A literature review and classification, Expert Systems with Applications, vol.36, issue.2, pp.2592-2602, 2009. ,
DOI : 10.1016/j.eswa.2008.02.021
Clustering Transactions with an Unbalanced Hierarchical Product Structure, 12th International Conference on Data Warehousing and Knowledge Discovery, pp.251-261, 2007. ,
DOI : 10.1007/978-3-540-74553-2_23
Adaptive Distances on Sets of Vectors, 2010 IEEE International Conference on Data Mining, pp.579-588, 2010. ,
DOI : 10.1109/ICDM.2010.45
Segmenting customer transactions using a pattern-based clustering approach, Third IEEE International Conference on Data Mining, pp.411-418, 2003. ,
DOI : 10.1109/ICDM.2003.1250947
An efficient data mining approach for discovering interesting knowledge from customer transactions, Expert Systems with Applications, vol.30, issue.4, pp.650-657, 2006. ,
DOI : 10.1016/j.eswa.2005.07.035
Clustering item data sets with association-taxonomy similarity, Third IEEE International Conference on Data Mining, pp.697-700, 2003. ,
DOI : 10.1109/ICDM.2003.1251011
URL : http://ntur.lib.ntu.edu.tw//bitstream/246246/200704191002930/1/01251011.pdf