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Conference Paper: An efficient algorithm for dense regions discovery from large-scale data streams
| Title | An efficient algorithm for dense regions discovery from large-scale data streams |
|---|---|
| Authors | |
| Issue Date | 2004 |
| Publisher | Springer. |
| Citation | 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2004), Sydney, Australia, 26-28 May 2004. In Advances in Knowledge Discovery and Data Mining:8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004: Proceedings, 2004, p. 116-120 How to Cite? |
| Abstract | © Springer-Verlag Berlin Heidelberg 2004. We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms. |
| Persistent Identifier | http://hdl.handle.net/10722/276480 |
| ISBN | |
| ISSN | 2023 SCImago Journal Rankings: 0.606 |
| Series/Report no. | Lecture Notes in Computer Science ; 3056 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Yip, Andy M. | - |
| dc.contributor.author | Wu, Edmond H. | - |
| dc.contributor.author | Ng, Michael K. | - |
| dc.contributor.author | Chan, Tony F. | - |
| dc.date.accessioned | 2019-09-18T08:33:44Z | - |
| dc.date.available | 2019-09-18T08:33:44Z | - |
| dc.date.issued | 2004 | - |
| dc.identifier.citation | 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2004), Sydney, Australia, 26-28 May 2004. In Advances in Knowledge Discovery and Data Mining:8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004: Proceedings, 2004, p. 116-120 | - |
| dc.identifier.isbn | 9783540220640 | - |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/276480 | - |
| dc.description.abstract | © Springer-Verlag Berlin Heidelberg 2004. We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on largescale data streams such as clickstreams are given which confirm that the usefulness of our algorithms. | - |
| dc.language | eng | - |
| dc.publisher | Springer. | - |
| dc.relation.ispartof | Advances in Knowledge Discovery and Data Mining:8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004: Proceedings | - |
| dc.relation.ispartofseries | Lecture Notes in Computer Science ; 3056 | - |
| dc.title | An efficient algorithm for dense regions discovery from large-scale data streams | - |
| dc.type | Conference_Paper | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1007/978-3-540-24775-3_14 | - |
| dc.identifier.scopus | eid_2-s2.0-7444246945 | - |
| dc.identifier.spage | 116 | - |
| dc.identifier.epage | 120 | - |
| dc.identifier.eissn | 1611-3349 | - |
| dc.publisher.place | Berlin | - |
| dc.identifier.issnl | 0302-9743 | - |