Logic-Based Association Rule Mining in XML Documents
| Autor: | John Zeleznikow, Hasan M. Jamil, Hong-Cheu Liu |
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| Rok vydání: | 2006 |
| Předmět: |
Document Structure Description
Information retrieval Association rule learning Computer science business.industry computer.internet_protocol Efficient XML Interchange XML Signature XML validation computer.file_format computer.software_genre Datalog XML framework XML database Knowledge base Knowledge extraction XML Schema Editor Information system XML schema business computer XML computer.programming_language |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783540311584 APWeb Workshops |
| DOI: | 10.1007/11610496_11 |
| Popis: | In this paper, we propose a new framework, called XLogic- Miner, to mine association rules from XML data. We consider the generate-and-test and the frequent-pattern growth approaches. In XLogic-Miner, we propose an novel method to represent a frequent-pattern tree in an object-relational table and exploit a new join operator developed in the paper. The principal focus of this research is to demonstrate that association rule mining can be expressed in an extended datalog program and be able to mine XML data in a declarative way. We also consider some optimization and performance issues. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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