PolyUCOMP: combining semantic vectors with skip bigrams for semantic textual similarity

Authors:
Jian Xu;Qin Lu;Zhengzhong Liu
Affiliations:
The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Venue:
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Year:
2012

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Abstract

This paper presents the work of the Hong Kong Polytechnic University (PolyUCOMP) team which has participated in the Semantic Textual Similarity task of SemEval-2012. The PolyUCOMP system combines semantic vectors with skip bigrams to determine sentence similarity. The semantic vector is used to compute similarities between sentence pairs using the lexical database WordNet and the Wikipedia corpus. The use of skip bigram is to introduce the order of words in measuring sentence similarity.