Algorithms for Intelligent Automated Evaluation of Relevance of Search Queries Results
This paper is devoted to the problem of automated evaluation of relevance of search queries results. High relevance of search algorithm output is the base of effective large quantities of data processing, which is worked at by users of modern informational systems. Automated and reliable estimate of relevance of search queries results will give the opportunity to lower time expenditures for the best algorithm choice. The usage of improved from this perspective algorithms will allow to raise effectiveness and user satisfaction when dealing with automatic search systems in any activities.
KeywordsNeural network Semantic analysis Algorithm Search query Teaching model Machine learning
This work was supported by Competitiveness Growth Program of the Federal Autonomous Educational Institution of Higher Professional Education National Research Nuclear University MEPhI (Moscow Engineering Physics Institute).
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