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- W2357304842 abstract "To solve the problems of that the traditional clustering algorithm was hard to obtain ideal result of Web user,and the indexes of current algorithms could't reflect user behavioral characteristic,this paper proposed a granular principle based clustering algorithm.It discretized the sparse data through a semi-fuzzy algorithm.Based on these,defined sparse similarity and initial equivalence relation on discrete data and designed variable precision quadratic clustering model to refine the result so the algorithm gained noise resistance ability.Defined a new clustering quantity evaluation model for the application field.The algorithm used multi indexes which could be used exclusively or together flexibly to evaluate the users.The experiment results show that the algorithm is suitable for Web user clustering and independent of data sequence,and provides results of various granular with high veracity and shows the data characteristics." @default.
- W2357304842 created "2016-06-24" @default.
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- W2357304842 date "2011-01-01" @default.
- W2357304842 modified "2023-09-22" @default.
- W2357304842 title "Granular principle based multi-index synthetical Web user clustering algorithm" @default.
- W2357304842 hasPublicationYear "2011" @default.
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