Mining association rules between sets of items in large databases
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OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Relationship extraction methods based on co-occurrence in web pages and files
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ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
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Since the Internet is sufficiently established, information on the Web is significantly enriched every day. It induces a fact that the information on Web pages has become increasingly useful in daily life. Therefore, it has become very common for us to refer to information on the Web, particularly when writing documents or programs. If we want to revisit the same Web pages to modify some part of a file later, it can be very hard to track down the Web pages originally referred to. In this paper, we propose methods for extracting relationships between files and Web pages based on the co-occurrence of data in Web-access logs and file-access logs. These relationships are very useful for revisiting Web pages related to target files. There are two approaches for merging the logs to analyse co-occurrence in these two types of access logs, involving a trade-off between accuracy and execution time. We call them the Pre-Merge and Post-Merge methods. We have evaluated these two methods using actual access logs.