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Proceedings ArticleDOI

Fuzzy genes: improving the effectiveness of information retrieval

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TLDR
An improvement in the effectiveness of information retrieval by using genetic algorithms (GAs) and fuzzy logic and a new weighting scheme based on fuzzy logic is presented for the first class of models.
Abstract
An improvement in the effectiveness of information retrieval by using genetic algorithms (GAs) and fuzzy logic is demonstrated. A new classification of information retrieval models within the framework of GAs is given. Such a classification is based on the target of the fitness function selected. When the aim of the optimization is document classification, we deal with document-oriented models. On the other hand, term-oriented models attempt to find those terms that are more discriminatory and adequate for user preferences to build a profile. A new weighting scheme based on fuzzy logic is presented for the first class of models. A comparison with other classical weighting schemes and a study of the best aggregation operators of the gene's local fitness to the overall fitness per chromosome are also presented. The deeper study of this new scheme in the term-oriented models is the main objective for future work.

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Citations
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Proceedings Article

Second Order Co-occurrence PMI for Determining the Semantic Similarity of Words

TL;DR: A new corpus-based method, called Second Order Co-occurrencePMI (SOC-PMI), uses Pointwise Mutual Information to sort lists of important neighbor words of the two target words to calculate the relative semantic similarity.
Journal ArticleDOI

Improving retrieval feedback with multiple term-ranking function combination

TL;DR: It is argued that the results of multiple functions can be merged, by analogy with ensembling classifiers, and present a simple combination technique based on the rank values of the suggested terms, which is effective not only with respect to unexpanded queries but also to any individual method, with notable improvements on the system's precision.
Journal ArticleDOI

Fuzzy information retrieval in WWW: a survey

TL;DR: This survey paper is an attempt to find some of the challenges faced by modern retrieval system in effective retrieval of information and different methodologies of fuzzy logic trying to make this mammoth and complex task simpler.
Journal ArticleDOI

A GA-based query optimization method for web information retrieval

TL;DR: Wang et al. as mentioned in this paper proposed a new GA-based query optimization method on relevance feedback for Web information retrieval based on three benchmark test collections Cranfield, Medline and CACM.
Book ChapterDOI

Intelligent filtering with genetic algorithms and fuzzy logic

TL;DR: Two different approaches combining fuzzy information retrieval of documents with genetic algorithms, and the pre-processing stage of classification called feature selection are presented, each based on a measure to find the most discriminatory terms.
References
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Book

Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book

Adaptation in natural and artificial systems

TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book

Introduction to Modern Information Retrieval

TL;DR: Reading is a need and a hobby at once and this condition is the on that will make you feel that you must read.
Book

Rough Sets: Theoretical Aspects of Reasoning about Data

TL;DR: Theoretical Foundations.
Journal ArticleDOI

A statistical interpretation of term specificity and its application in retrieval

TL;DR: It is argued that terms should be weighted according to collection frequency, so that matches on less frequent, more specific, terms are of greater value than matches on frequent terms.
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