Abstract
AbstractConceptual inference on texts with natural language processing is one of the most important topics of artificial intelligence. The meaning extraction process with artificial intelligence algorithms is frequently done in foreign languages, and in recent years studies for Turkish have been increasing. In this study, concept-meaning extraction studies made for Turkish have been researched and extraction algorithms which can be done on the computer network concept dictionary have been investigated.
 Keywords: artificial intelligence, wordnet, algorithms, dictionary, network.
Highlights
Natural language processing (NLP) is one of the lower branches of artificial intelligence, and language works with areas such as shape and meaning
The second study aims to present concepts on the works that can be used on ontological dictionary created in another study by extracting concepts from Turkish Wordnet, Turkish Informatics Society, Turkish Language Association dictionary and computer network books
It has been seen that clustering performance has been improved by removing symbolic information from Wordnet ontology with the hypernyms significant vector model emerging from these three models
Summary
Natural language processing (NLP) is one of the lower branches of artificial intelligence, and language works with areas such as shape and meaning. Together with developing information projects, work in the field of NDP is increasing rapidly. The Balkanet project has been developed as a Wordnet subproject with Balkan languages and Turkish (Bilgin, Cetinoglu & Oflazer, 2004). Firstly; Studies conducted for Turkish Wordnet and related texts have been examined. The second study aims to present concepts on the works that can be used on ontological (conceptual) dictionary created in another study by extracting concepts from Turkish Wordnet, Turkish Informatics Society, Turkish Language Association dictionary and computer network books. In studies conducted for the Turkish language (Oflazer, Say, Hakkani-Tur & Tur, 2003; Oflazer, 2003; Hakkani-Tur, Tur & Oflazer, 2002), the words are grouped into shooting groups. The study aims to separate the words on the quoted text and to work on their roots
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