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- W148945521 abstract "Clickstream analysis can reveal usage patterns on company’s web sites giving highly improved understanding of customer behaviour, which can be used to improve customer satisfaction with the website and the company in general, yielding a great business advantage. Such summary information and rules have to be extracted from very large collections of clickstreams in web sites. This is challenging data mining, both in terms of the magnitude of data involved, and the need to incrementally adapt the mined patterns and rules as new data is collected. In this paper, we present some guidelines for implementing on-line analytical mining (OLAM) engines which means an integration of OLAP and mining techniques for exploring multidimensional data cube structures. In addition, we describe a data cube alternative for analyzing clickstreams. Besides, we discussed implementations that we consider efficient approaches on exploring multidimensional data cube structures, such as DBMiner, WebLobMiner, and OLAP-based Web Access" @default.
- W148945521 created "2016-06-24" @default.
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- W148945521 date "2004-01-01" @default.
- W148945521 modified "2023-09-27" @default.
- W148945521 title "MINING CLICKSTREAM-BASED DATA CUBES" @default.
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- W148945521 doi "https://doi.org/10.5220/0002631305830586" @default.
- W148945521 hasPublicationYear "2004" @default.
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