Coordinate Indexing Algorithms Taking Into Account the Classification Signs-terms in the Subject Area

2022

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DOI 10.33693/2313-223x-2022-9-1-21-31
Data confidence 70 medium
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Abstract

Libraries and Internet searchers are becoming increasingly frustrated with topical access results, in part because of the unmanageability of a wide range of search engines. The need to improve accuracy and limit the size of search queries was the main motivation for this study. The purpose of this article is to explore coordinate indexing algorithms taking into account the classification features-terms in the subject area. The study was written using the material modelling method (mathematical): pre-existing models were used, which offer partial coordination as fundamental to confirm their effectiveness in practice. The measurement method was used to analyse the numerical results. In the presented study, the features and characteristics of partial coordination were presented. In addition, the benefits of partial coordination have been studied. The methodology proposed by the authors focuses on the benefits of a “smart” query that can be executed in an OPAC environment without further effort on the part of the user; the user enters their keywords as before, but “smart” keyword coordination in documents avoids unsuitable partial matches. It was concluded that the order of ranking of documents on the subject should be included in the same way with those unverified records lacking partial coordination of partial documents.