A Novel Approach to Improve Users Search Goal in Web Usage Mining

Autor: R. Lokeshkumar, P. Sengottuvelan
Jazyk: angličtina
Rok vydání: 2015
Předmět:
DOI: 10.5281/zenodo.1108819
Popis: Web mining is to discover and extract useful Information. Different users may have different search goals when they search by giving queries and submitting it to a search engine. The inference and analysis of user search goals can be very useful for providing an experience result for a user search query. In this project, we propose a novel approach to infer user search goals by analyzing search web logs. First, we propose a novel approach to infer user search goals by analyzing search engine query logs, the feedback sessions are constructed from user click-through logs and it efficiently reflect the information needed for users. Second we propose a preprocessing technique to clean the unnecessary data's from web log file (feedback session). Third we propose a technique to generate pseudo-documents to representation of feedback sessions for clustering. Finally we implement k-medoids clustering algorithm to discover different user search goals and to provide a more optimal result for a search query based on feedback sessions for the user.
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Databáze: OpenAIRE
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