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Conference Paper: Discretization of Multidimensional Web Data for Informative Dense Regions Discovery
Title | Discretization of Multidimensional Web Data for Informative Dense Regions Discovery |
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Authors | |
Keywords | Dense regions discovery Discretization Web mining Web information system |
Issue Date | 2004 |
Publisher | Springer. |
Citation | First International Conference on Computational and Information Science (CIS 2004), Shanghai, China, 16-18 December 2004. In Computational and Information Science: First International Symposium, CIS 2004, Shanghai, China, December 16-18, 2004: Proceedings, 2004, p. 718-724 How to Cite? |
Abstract | Dense regions discovery is an important knowledge discovery process for finding distinct and meaningful patterns from given data. The challenge in dense regions discovery is how to find informative patterns from various types of data stored in structured or unstructured databases, such as mining user patterns from Web data. Therefore, novel approaches are needed to integrate and manage these multi-type data repositories to support new generation information management systems. In this paper, we focus on discussing and purposing several discretization methods for large matrices. The experiments suggest that the discretization methods can be employed in practical Web applications, such as user patterns discovery. © Springer-Verlag 2004. |
Persistent Identifier | http://hdl.handle.net/10722/276817 |
ISBN | |
ISSN | 2023 SCImago Journal Rankings: 0.606 |
Series/Report no. | Lecture Notes in Computer Science ; 3314 |
DC Field | Value | Language |
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dc.contributor.author | Wu, Edmond H. | - |
dc.contributor.author | Ng, Michael K. | - |
dc.contributor.author | Yip, Andy M. | - |
dc.contributor.author | Chan, Tony F. | - |
dc.date.accessioned | 2019-09-18T08:34:45Z | - |
dc.date.available | 2019-09-18T08:34:45Z | - |
dc.date.issued | 2004 | - |
dc.identifier.citation | First International Conference on Computational and Information Science (CIS 2004), Shanghai, China, 16-18 December 2004. In Computational and Information Science: First International Symposium, CIS 2004, Shanghai, China, December 16-18, 2004: Proceedings, 2004, p. 718-724 | - |
dc.identifier.isbn | 9783540241270 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/10722/276817 | - |
dc.description.abstract | Dense regions discovery is an important knowledge discovery process for finding distinct and meaningful patterns from given data. The challenge in dense regions discovery is how to find informative patterns from various types of data stored in structured or unstructured databases, such as mining user patterns from Web data. Therefore, novel approaches are needed to integrate and manage these multi-type data repositories to support new generation information management systems. In this paper, we focus on discussing and purposing several discretization methods for large matrices. The experiments suggest that the discretization methods can be employed in practical Web applications, such as user patterns discovery. © Springer-Verlag 2004. | - |
dc.language | eng | - |
dc.publisher | Springer. | - |
dc.relation.ispartof | Computational and Information Science: First International Symposium, CIS 2004, Shanghai, China, December 16-18, 2004: Proceedings | - |
dc.relation.ispartofseries | Lecture Notes in Computer Science ; 3314 | - |
dc.subject | Dense regions discovery | - |
dc.subject | Discretization | - |
dc.subject | Web mining | - |
dc.subject | Web information system | - |
dc.title | Discretization of Multidimensional Web Data for Informative Dense Regions Discovery | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-540-30497-5_112 | - |
dc.identifier.scopus | eid_2-s2.0-35048898038 | - |
dc.identifier.spage | 718 | - |
dc.identifier.epage | 724 | - |
dc.identifier.eissn | 1611-3349 | - |
dc.publisher.place | Berlin | - |
dc.identifier.issnl | 0302-9743 | - |