Similarity identification algorithm of hard-structured data based on semantic networks
DOI:
https://doi.org/10.15587/1729-4061.2015.51051Keywords:
search algorithm, bibliographic description, similarity search, semantic networksAbstract
The main disadvantage of any similarity search algorithm is its purpose. Existing algorithms are focused purely on the text as a continuous element of structural data and do not take into account the context of information that is presented in the text. This makes it impossible to use algorithms for text with a specific context. The only application of such algorithms is the texts that can be elements of a more complex object of comparison. The paper presents a similarity search algorithm of hard-structured data using semantic networks. The built semantic network takes into account all the features of the bibliographic description of the publication and is endowed with methods of comparison of its separate parts. Application of the algorithm for similarity search of bibliographic descriptions in the information-analytical system "ScienceLP" was investigated. The research results have confirmed the usefulness of the developed algorithm for effective relevant search. For the versatility of the software implementation of the algorithm, reflection-oriented programming approach was used. Such an approach allows to identify almost any object, no matter whether it is built-in or user data type. This allows the algorithm to be independent of the type of the compared object and its internal structure.
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Copyright (c) 2015 Руслан Богданович Тушницький, Володимир Мирославович Макар
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