Semantic Relation’s Weight Determination on a Graph Based WordNet

Yıl 2018, CMES 2018 Ek Sayısı, 67 - 78, 30.11.2018

Çağatay Tülü , Umut Orhan Erhan Turan

https://doi.org/10.17714/gumusfenbil.432582

Öz

Determination
of semantic relatedness between two textual items is one of the crucial phases
in many Natural Language Processing applications. In this study, a new approach to lexicon based semantic
relation determination methods was
experienced using WordNet 3.0 and Men’s real-life
similarity dataset. Men’s test collection was used for the determination of the
relation weights and determined weights were used in semantic relatedness
computation. RG65 similarity dataset was used for a benchmark of the proposed method and Spearman correlation 0.81 was
gained, taking into account that retrieving the relations weight using a large
scale dataset and testing them with another real-life
dataset promises new perspectives to the determination of the relations weight and to the relatedness computation.

Anahtar Kelimeler

Natural language processing, Semantic relation, WordNet

Çizge Tabanlı WordNet Ağı Üzerinde Anlamsal İlişki Ağırlıklarının Tespiti

Öz

Birçok
doğal dil işleme uygulamasında metinsel iki öğenin anlamsal ilişkisinin tespit
edilmesi çok önemli bir aşamadır. Bu çalışmada WordNet 3.0 ve Men’s veri seti
kullanarak sözlük tabanlı anlamsal ilişki belirleme metodları için yeni bir
yaklaşım sunulmaktadır. Anlamsal ağırlıkların hesaplanmasında Men’s veriseti
kullanılmış ve bulunan değerler anlamsal ağırlık hesaplanmasında
kullanılmıştır. Önerilen metodun doğruluğunu ölçmek için RG65 benzerlik
veriseti kullanılmış, kayıslama sonucunda 0.81 Spearman korelasyon değeri elde
edilmiştir. Büyük boyutlu bir verisetinin geliştirme ve test için kullanılıp,
diğer önemli bir verisetinin de kıyaslama amaçlı olarak anlamsal ilişki
tiplerinin ağırlıklarının belirlenmesi ve anlamsal ilişkinin hesaplanmasında
kullanılması anlamsal benzerlik ve anlamsal ilişki hesaplanmasına farklı bir
bakış açısı getirmektedir.

Anahtar Kelimeler

Doğal dil işleme, Anlamsal ilişki, WordNet

Kaynakça

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