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- W2001034259 abstract "Clustering of data in a large dimension space is of great interest in many data mining applications. In this paper, we propose a method for clustering of web usage data in a high-dimensional space based on a concept hierarchy model. In this method, the relationship present in the web usage data are mapped into a fuzzy proximity relation of user transactions. We also described an approach to present the preference set of URLs to a new user transaction based on the match score with the clusters. The study demonstrates that our approach is general and effective for mining the web data for web personalization." @default.
- W2001034259 created "2016-06-24" @default.
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- W2001034259 date "2002-09-01" @default.
- W2001034259 modified "2023-09-26" @default.
- W2001034259 title "MINING WEB DATA USING CLUSTERING TECHNIQUE FOR WEB PERSONALIZATION" @default.
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- W2001034259 doi "https://doi.org/10.1142/s1469026802000580" @default.
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