Patterns between words are generally used for automatic information extraction. However, the patterns can only find related words close to each other. In this study, a method based on substitute vectors can overcome of this difficulty. Firstly, the word sets having the same substitute vector are constructed. Then, similar word sets are obtained according to the number of co-occurring sets. In this sets, semantically relatedness ratio is above 70%. The proposed method is unsupervised. Because, it does not require any seed words manually labeled.
Automatic information extraction discovery of similar words synonyms near-synonyms substitute vectors natural language processing artificial intelligence.
Birincil Dil | İngilizce |
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Bölüm | Research Articles |
Yazarlar | |
Yayımlanma Tarihi | 1 Mart 2016 |
Gönderilme Tarihi | 4 Kasım 2013 |
Yayımlandığı Sayı | Yıl 2016 Cilt: 34 Sayı: 1 |
IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/