文件名称:Semantic_Session_Analysis_for_Web_Usage_Mining
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A semantic session analysis method partitioning Web usage logs is presented．Semantic W eb usage log preparation model enhances usage logs with semantic．The M arkov chain
mode1 based on ontology semantic measurement is used to identi．
ing which active session a request should belong to．The corn—
petitive method is applied to determine the end of the sessions．
Compared with other algorithms，more successfu1 sessions are additionally detected by semantic outlier analysis．-A semantic session analysis method partitioning Web usage logs is presented. Semantic W eb usage log preparation model enhances usage logs with semantic. The M arkov chainmode1 based on ontology semantic measurement is used to identi. ing which active session a request should belong to. The corn-petitive method is applied to determine the end of the sessions. Compared with other algorithms, more successfu1 sessions are additionally detected by semantic outlier analysis.
mode1 based on ontology semantic measurement is used to identi．
ing which active session a request should belong to．The corn—
petitive method is applied to determine the end of the sessions．
Compared with other algorithms，more successfu1 sessions are additionally detected by semantic outlier analysis．-A semantic session analysis method partitioning Web usage logs is presented. Semantic W eb usage log preparation model enhances usage logs with semantic. The M arkov chainmode1 based on ontology semantic measurement is used to identi. ing which active session a request should belong to. The corn-petitive method is applied to determine the end of the sessions. Compared with other algorithms, more successfu1 sessions are additionally detected by semantic outlier analysis.
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Semantic_Session_Analysis_for_Web_Usage_Mining.pdf