Open AccessComparison of Templates with Word2vec in Finding Semantic Relations Between Words
Author(s) -
Kaan Ant,
Uğur Soğukpınar,
Mehmet Fatih Amasyalı
Publication year - 2018
Publication title -
akıllı sistemler ve uygulamaları dergisi
Language(s) - English
Resource type - Journals
ISSN - 2667-6893
DOI - 10.54856/jiswa.201805007
Subject(s) - 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 , cognition , embedding , neuroscience
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.