Journal Article

·2018 OPEN ACCESS

Comparison of Templates with Word2vec in Finding Semantic Relations Between Words

Kaan Ant YTU , Ugur Sogukpinar YTU , Mehmet Fatif Amasyali YTU

Journal of Intelligent Systems with Applications

Abstract

The use of databases those containing semantic relationships between words is becoming increasingly widespread in order to make natural language processing work more effective. Instead of the word-bag approach, the suggested semantic spaces give the distances between words, but they do not express the relation types. In this study, it is shown how semantic spaces can be used to find the type of relationship and it is compared with the template method. According to the results obtained on a very large scale, while is_a and opposite are more successful for semantic spaces for relations, the approach of templates is more successful in the relation types at_location, made_of and non relational.

Keywords

Word2vec Computer science Relation (database) Semantic relation Natural language processing Semantic similarity Template Artificial intelligence Information retrieval Semantic computing Semantic Web Data mining Psychology Programming language

Subject Areas

Natural Language Processing Techniques ·Artificial Intelligence ·Physical Sciences
Topic Modeling ·Artificial Intelligence ·Physical Sciences
Advanced Text Analysis Techniques ·Artificial Intelligence ·Physical Sciences

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