A temporal comparison of AltaVista Web searching: Research Articles
Journal of the American Society for Information Science and Technology
Lexical query paraphrasing for document retrieval
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Journal of Global Optimization
Implicit User Modelling Using Hybrid Meta-Heuristics
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
Bees Swarm Optimization Based Approach for Web Information Retrieval
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
New inspirations in swarm intelligence: a survey
International Journal of Bio-Inspired Computation
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Searching for information on the Web has become one of our most important and frequent activities. Sometimes, Web users may formulate a search query based upon their different levels of expertise or background knowledge, which may obscure some useful documents in retrieving results because the query vocabulary differs from the vocabulary within a particular document's collection. This raises the need for automatic query paraphrasing to generate different vocabulary term possibilities. In this study, we will improve a query paraphrasing technique using the artificial bee colony (ABC) algorithm in order to generate the most reliable paraphrased query from the initial search query automatically and without user supervision. Our proposed method shows an improvement in information retrieval performance compared with the genetic algorithm query paraphrasing system.