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dc.contributorMühendislik Fakültesi / Faculty of Engineering Bilgisayar Mühendisliği / Computer Engineeringtr_TR
dc.contributor.authorİlgen, Bahar
dc.contributor.authorAdalı, Eşref
dc.contributor.authorTantuğ, Ahmet Cüneyd
dc.description.abstractWord Sense Disambiguation (WSD) is the task of choosing the most appropriate sense of a word having multiple senses in a given context. Collocational features acquired from the words in neighborship with the ambiguous word are one of the important knowledge sources in this area. This paper explores the effective sets of collocational features in Turkish in order to obtain better Turkish WSD systems. A lexical sample dataset of highly polysemous nouns and verbs has been prepared as the initial step of the work. Several supervised learning algorithms have been tested on this data by supplying different feature sets to select the best performing features for both nouns and verbs in Turkish. Also, we investigated the impact of several collocational features of polysemous words and evaluated the performance of several supervised machine learning algorithms.tr_TR
dc.relationIn Intelligent Engineering Systems (INES)tr_TR
dc.subjectWord Sense Disambiguationtr_TR
dc.subjectfeature selectiontr_TR
dc.subjectmachine learningtr_TR
dc.titleThe impact of collocational features in Turkish Word Sense Disambiguation.tr_TR

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