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On Using Genetic Algorithms for Multimodal Relevance Optimization in Information Retrieval.
Peer reviewed Peer reviewed
Boughanem, M.; Christment, C.; Tamine, L. – Journal of the American Society for Information Science and Technology, 2002
Presents a genetic relevance optimization process performed in an information retrieval system that uses genetic techniques for solving multimodal problems (niching) and query reformulation techniques. Explains that the niching technique allows the process to reach different relevance regions of the document space, and that query reformulations…
Descriptors: Algorithms, Genetics, Information Retrieval, Relevance (Information Retrieval)
A Fuzzy Genetic Algorithm Approach to an Adaptive Information Retrieval Agent.
Peer reviewed Peer reviewed
Martin-Bautista, Maria J.; Vila, Maria-Amparo; Larsen, Henrik Legind – Journal of the American Society for Information Science, 1999
Presents an approach to a Genetic Information Retrieval Agent Filter (GIRAF) that filters and ranks documents retrieved from the Internet according to users' preferences by using a Genetic Algorithm and fuzzy set theory to handle the imprecision of users' preferences and users' evaluation of the retrieved documents. (Author/LRW)
Descriptors: Algorithms, Genetics, Information Retrieval, Internet
Genetic Algorithm-Based Relevance Feedback for Image Retrieval Using Local Similarity Patterns.
Peer reviewed Peer reviewed
Stejic, Zoran; Takama, Yasufumi; Hirota, Kaoru – Information Processing & Management, 2003
Proposes local similarity pattern (LSP) as a new method for computing digital image similarity. Topics include optimizing similarity computation based on genetic algorithm; relevance feedback; and an evaluation of LSP on five databases that showed an increase in retrieval precision over other methods for computing image similarity. (Author/LRW)
Descriptors: Algorithms, Databases, Evaluation Methods, Genetics
Order-Based Fitness Functions for Genetic Algorithms Applied to Relevance Feedback.
Peer reviewed Peer reviewed
Lopez-Pujalte, Cristina; Guerrero-Bote, Vicente P.; de Moya-Anegon, Felix – Journal of the American Society for Information Science and Technology, 2003
Discusses genetic algorithms in information retrieval, especially for relevance feedback, and evaluates the efficacy of a genetic algorithm with various order-based fitness functions for relevance feedback in a test database. Compares results with the Ide dec-hi method, one of the best traditional methods. (Contains 56 references.) (Author/LRW)
Descriptors: Algorithms, Comparative Analysis, Databases, Genetics
Multiple Query Evaluation Based on an Enhanced Genetic Algorithm.
Peer reviewed Peer reviewed
Tamine, Lynda; Chrisment, Claude; Boughanem, Mohand – Information Processing & Management, 2003
Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…
Descriptors: Algorithms, Comparative Analysis, Evolution, Genetics
A Test of Genetic Algorithms in Relevance Feedback.
Peer reviewed Peer reviewed
Lopez-Pujalte, Cristina; Guerrero Bote, Vicente P.; Moya Anegon, Felix de – Information Processing & Management, 2002
Discussion of information retrieval, query optimization techniques, and relevance feedback focuses on genetic algorithms, which are derived from artificial intelligence techniques. Describes an evaluation of different genetic algorithms using a residual collection method and compares results with the Ide dec-hi method (Salton and Buckley, 1990…
Descriptors: Algorithms, Artificial Intelligence, Comparative Analysis, Evaluation Methods