Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Probabilistic and genetic algorithms in document retrieval
Communications of the ACM
Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
An example-based mapping method for text categorization and retrieval
ACM Transactions on Information Systems (TOIS)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Information Processing and Management: an International Journal
On the merits of building categorization systems by supervised clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Applying genetic algorithms to query optimization in document retrieval
Information Processing and Management: an International Journal
A probabilistic model of information retrieval: development and comparative experiments Part 2
Information Processing and Management: an International Journal
Communications of the ACM
Evaluating document clustering for interactive information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Information Retrieval: Algorithms and Heuristics
Information Retrieval: Algorithms and Heuristics
Query Optimization in Information Retrieval Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Query expansion using associated queries
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Facing the huge amount of information available on the world wide web, people suffer from spending much time and effort to examine the results provided by a search engine. This is mainly because of searching without considering the users' preference and history of uses. Although some search engines have been developed and are currently used, without information regarding users' desire and profile, the search domain remains too large to be effective. This paper proposes a search method that operates on a database of e-documents with references of a common body of knowledge and the retrieval information of the users. By employing data mining and optimization techniques, a framework for an information retrieval system that can effectively search content-related documents is proposed. The concept with the proposed algorithm is described with an illustrative algorithm.