Abstract
This paper develops methods for calculating the semantic similarity (closeness)-relatedness of natural language words. The concept of semantic relatedness allows one to construct algorithmic models for the context-linguistic analysis with a view to solving problems such as word sense disambiguation, named entity recognition, natural language text analysis, etc. A new algorithm is proposed for estimating the semantic distance between natural language words. This method is a weighted modification of the well-known Lesk approach based on the lexical intersection of glossary entries.
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