Characterizing Sequences of User Actions for Access Logs Analysis
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The paper presents new measures for characterizing sequences of user actions. They are aimed at categorizing user behavior on intranet sites. Their relevance is evaluated using different encoding and clustering algorithms. New criteria are introduced for comparing clustering methods.
KeywordsMutual Information User Action Cluster Distribution Exponential Regression Model Base Similarity Measure
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