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Conference Paper: An efficient multidimensional data model for web usage mining
Title | An efficient multidimensional data model for web usage mining |
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Authors | |
Issue Date | 2004 |
Publisher | Springer. |
Citation | 6th Asia-Pacific Web Conference (APWeb 2004), Hangzhou, China, 14-17 April 2004. In Advanced Web Technologies and Applications: 6th Asia-Pacific Web Conference, APWeb 2004, Hangzhou, China, April 14-17, 2004. Proceedings, 2004, p. 373-383 How to Cite? |
Abstract | Web applications such as personalization and recommendation have raised the concerns of people because they are crucial to improve customer services, particularly for E-commerce Websites. Understanding customer preferences and requirements in time is a premise to optimize these Web services. In this paper, a new data model for Web data is introduced to analyze user behavior. The merit of the cube model is that it not only aggregates user access information but also takes the Web structure information into account. Based on the model, we propose some solutions to intelligently discover interesting user access patterns for Website optimization, Web personalization and recommendation. We used the Web usage data from a sports Website in China to evaluate the effectiveness of the model. The results show that this integrated data model is effective and efficient to apply into practical Web applications. © Springer-Verlag Berlin Heidelberg 2004. |
Persistent Identifier | http://hdl.handle.net/10722/276818 |
ISBN | |
ISSN | 2020 SCImago Journal Rankings: 0.249 |
Series/Report no. | Lecture Notes in Computer Science ; 3007 |
DC Field | Value | Language |
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dc.contributor.author | Wu, Edmond H. | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Huang, Joshua Z. | - |
dc.date.accessioned | 2019-09-18T08:34:45Z | - |
dc.date.available | 2019-09-18T08:34:45Z | - |
dc.date.issued | 2004 | - |
dc.identifier.citation | 6th Asia-Pacific Web Conference (APWeb 2004), Hangzhou, China, 14-17 April 2004. In Advanced Web Technologies and Applications: 6th Asia-Pacific Web Conference, APWeb 2004, Hangzhou, China, April 14-17, 2004. Proceedings, 2004, p. 373-383 | - |
dc.identifier.isbn | 9783540213710 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276818 | - |
dc.description.abstract | Web applications such as personalization and recommendation have raised the concerns of people because they are crucial to improve customer services, particularly for E-commerce Websites. Understanding customer preferences and requirements in time is a premise to optimize these Web services. In this paper, a new data model for Web data is introduced to analyze user behavior. The merit of the cube model is that it not only aggregates user access information but also takes the Web structure information into account. Based on the model, we propose some solutions to intelligently discover interesting user access patterns for Website optimization, Web personalization and recommendation. We used the Web usage data from a sports Website in China to evaluate the effectiveness of the model. The results show that this integrated data model is effective and efficient to apply into practical Web applications. © Springer-Verlag Berlin Heidelberg 2004. | - |
dc.language | eng | - |
dc.publisher | Springer. | - |
dc.relation.ispartof | Advanced Web Technologies and Applications: 6th Asia-Pacific Web Conference, APWeb 2004, Hangzhou, China, April 14-17, 2004. Proceedings | - |
dc.relation.ispartofseries | Lecture Notes in Computer Science ; 3007 | - |
dc.title | An efficient multidimensional data model for web usage mining | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-540-24655-8_40 | - |
dc.identifier.scopus | eid_2-s2.0-35048899695 | - |
dc.identifier.spage | 373 | - |
dc.identifier.epage | 383 | - |
dc.identifier.eissn | 1611-3349 | - |
dc.publisher.place | Berlin | - |
dc.identifier.issnl | 0302-9743 | - |