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Journals / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2016 / Cilt: 34 - Sayı: 1

AUTOMATIC DISCOVERY OF SIMILAR WORDS BY SUBSTITUTE VECTORS

İnci DÜZENLİ
M. Fatih AMASYALI
Pages
125–133
Publication Date
2016-03-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Because, it does not require any seed words manually labeled.

📌 3 Key Takeaways

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Objective & Hypothesis:Patterns between words are generally used for automatic information extraction.
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Key Findings & Data:In this sets, semantically relatedness ratio is above 70%.
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Conclusion & Impact:Because, it does not require any seed words manually labeled.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Automatic information extraction · discovery of similar words · synonyms

Abstract

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.

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Cite This Article

DÜZENLİ, İ., AMASYALI, M. F. (2016). AUTOMATIC DISCOVERY OF SIMILAR WORDS BY SUBSTITUTE VECTORS. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 34 - Sayı: 1, 125–133. https://ajindex.com/articles/419453

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