Details

Autor(en) / Beteiligte

• Sajadi, Armin
• Milios, Evangelos E.
• Keselj, Vlado

Titel

Vector Space Representation of Concepts Using Wikipedia Graph Structure

Ist Teil von

• Natural Language Processing and Information Systems, p.393-405

Ort / Verlag

Cham: Springer International Publishing

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• We introduce a vector space representation of concepts using Wikipedia graph structure to calculate semantic relatedness. The proposed method starts from the neighborhood graph of a concept as the primary form and transfers this graph into a vector space to obtain the final representation. The proposed method achieves state of the art results on various relatedness datasets. Combining the vector space representation with standard coherence model, we show that the proposed relatedness method performs successfully in Word Sense Disambiguation (WSD). We then suggest a different formulation for coherence to demonstrate that, in a short enough sentence, there is one key entity that can help disambiguate every other entity. Using this finding, we provide a vector space based method that can outperform the standard coherence model in a significantly shorter computation time.