Genetic algorithm implementation for effective document subject search

This paper describes the software implementation of genetic algorithm for identifying and selecting most relevant results received during sequentially executed subject search operations. Simulated evolutionary process generates sustainable and effective population of search queries, forms search pat...

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Published in:arXiv.org
Main Authors: Ivanov, V K, Meskin, P I
Format: Paper
Language:English
Published: Ithaca Cornell University Library, arXiv.org 16.04.2015
Subjects:
Computer simulation
Fitness
Genetic algorithms
Searching
ISSN:2331-8422
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Abstract This paper describes the software implementation of genetic algorithm for identifying and selecting most relevant results received during sequentially executed subject search operations. Simulated evolutionary process generates sustainable and effective population of search queries, forms search pattern of documents or semantic core, creates relevant sets of required documents, allows automatic classification of search results. The paper discusses the features of subject search, justifies the use of a genetic algorithm, describes arguments of the fitness function and describes basic steps and parameters of the algorithm.
AbstractList This paper describes the software implementation of genetic algorithm for identifying and selecting most relevant results received during sequentially executed subject search operations. Simulated evolutionary process generates sustainable and effective population of search queries, forms search pattern of documents or semantic core, creates relevant sets of required documents, allows automatic classification of search results. The paper discusses the features of subject search, justifies the use of a genetic algorithm, describes arguments of the fitness function and describes basic steps and parameters of the algorithm.
Author Meskin, P I
Ivanov, V K
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Title Genetic algorithm implementation for effective document subject search
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