XAR-Miner: efficient association rules mining for XML data
Paper
Paper/Presentation Title | XAR-Miner: efficient association rules mining for XML data |
---|---|
Presentation Type | Paper |
Authors | Zhang, Sheng (Author), Zhang, Ji (Author), Liu, Han (Author) and Wang, Wei (Author) |
Editors | Ellis, Allan and Hagino, Tatsuya |
Journal or Proceedings Title | Proceedings of the 14th International World Wide Web Conference (WWW'05) |
Number of Pages | 2 |
Year | 2005 |
Place of Publication | New York, NY, USA |
ISBN | 1595930469 |
Web Address (URL) of Paper | http://www2005.org/ |
Conference/Event | 14th International World Wide Web Conference (WWW'05) |
Event Details | 14th International World Wide Web Conference (WWW'05) Event Date 10 to end of 14 May 2005 Event Location Chiba, Japan |
Abstract | [Abstract]: In this paper, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently. In XAR-Miner, raw data in the XML document are first preprocessed to transform to either an Indexed Content Tree (IX-tree) or Multi-relational databases (Multi-DB), depending on the size of XML document and memory constraint of the system, for efficient data selection |
Keywords | association rule mining, XML data, meta-patterns |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Nanjing Normal University, China |
University of Toronto, Canada |
https://research.usq.edu.au/item/9z290/xar-miner-efficient-association-rules-mining-for-xml-data
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