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Computing Semantic Similarity for Vietnamese Concepts Using Wikipedia

  • Hien T. NguyenEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 341)

Abstract

Evaluating semantic similarity between concepts is a very common component in many applications dealing with textual data such as information extraction, information retrieval, natural language processing, or knowledge acquisition. This paper presents an approach to assess semantic similarity between Vietnamese concepts using Vietnamese Wikipedia. Firstly, the Vietnamese Wikipedia’ structure is exploited to derive a Vietnamese ontology. Next, based on the obtained ontology, we employ similarity measures in literature to evaluate the semantic similarity between Vietnamese concepts. Then we conduct an experiment providing 30 Vietnamese concept pairs to 18 human subjects to assess similarity of these pairs. Finally, we use Pearson product-moment correlation coefficient to estimate the correlation between human judgments and the results of similarity measures employed. The experiment results show that our system achieves quite good performance and that similarity measures between Vietnamese concepts are potential in enhancing the performance of applications dealing with textual data.

Keywords

Similarity Measure Semantic Similarity Semantic Relatedness Short Path Length Concept Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam

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