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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| Veröffentlicht in: | arXiv.org |
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| Hauptverfasser: | , |
| Format: | Paper |
| Sprache: | Englisch |
| Veröffentlicht: |
Ithaca
Cornell University Library, arXiv.org
16.04.2015
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| Schlagworte: | |
| ISSN: | 2331-8422 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | 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. |
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| Bibliographie: | SourceType-Working Papers-1 ObjectType-Working Paper/Pre-Print-1 content type line 50 |
| ISSN: | 2331-8422 |
| DOI: | 10.48550/arxiv.1504.04216 |