Rough sets based reasoning and pattern mining for a two-stage information filtering system
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Pattern mining for a two-stage information filtering system
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
A two-stage decision model for information filtering
Decision Support Systems
Intelligent Information Retrieval Using Fuzzy Association Rule Classifier
International Journal of Intelligent Information Technologies
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The amount of Web information is growing rapidly, improving the efficiency and accuracy of Web information retrieval is uphill battle. There are two fundamental issues regarding the effectiveness of Web information gathering: information mismatch and overload. To tackle these difficult issues, an integrated information filtering and sophisticated data processing model has been presented in this paper. In the first phase of the proposed scheme, an information filter that based on user search intents was incorporated in Web search process to quickly filter out irrelevant data. In the second data processing phase, a pattern taxonomy model (PTM) was carried out using the reduced data. PTM rationalizes the data relevance by applying data mining techniques that involves more rigorous computations. Several experiments have been conducted and the results show that more effective and efficient access Web information has been achieved using the new scheme.