Abstract
With the sheer amount of data stored, presented and exchanged using XML nowadays, the ability to extract knowledge from XML data sources becomes increasingly important and desirable. This paper aims to integrate the newly emerging XML technology with data mining technology, using association rule mining as a case in point. Compared with traditional association mining in the well-structured world (e.g., relational databases), mining from XML data is faced with more challenges due to the inherent flexibilities of XML in both structure and semantics. The primary challenges include 1) a more complicated hierarchical data structure; 2) an ordered data context; and 3) a much bigger data size. To tackle these challenges, in this paper, we propose an extended XML-enabled association rule framework, which is flexible and powerful enough to represent both simple and complex structured association relationships inherent in XML data.
Original language | English |
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Title of host publication | Database and Expert Systems Applications |
Subtitle of host publication | 14th International Conference, DEXA 2003, Prague, Czech Republic, September 1-5, 2003. Proceedings |
Editors | Vladimir Marik, Werner Retschitzegger, Olga Stepankova |
Pages | 88-97 |
Number of pages | 10 |
ISBN (Electronic) | 978-3-540-45227-0 |
DOIs | |
Publication status | Published - Sept 2003 |
Event | 14th International Conference on Database and Expert Systems Applications, DEXA 2003 - Prague, Czech Republic Duration: 1 Sept 2003 → 5 Sept 2003 Conference number: 14 |
Publication series
Name | Lecture notes in computer science |
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Volume | 2736 |
Conference
Conference | 14th International Conference on Database and Expert Systems Applications, DEXA 2003 |
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Abbreviated title | DEXA |
Country/Territory | Czech Republic |
City | Prague |
Period | 1/09/03 → 5/09/03 |
Keywords
- DB-DM: DATA MINING
- IR-63502
- EWI-7214