Semantic Relatedness Measure for Identifying Relevant Answers in Online Community Question Answering Services

Lee, Jun Choi and Cheah, Yu-N (2015) Semantic Relatedness Measure for Identifying Relevant Answers in Online Community Question Answering Services. In: 9th International Conference on Information Technology in Asia, 4th - 5th August 2015, Hilton Hotel, Kuching.

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Abstract

This study introduces a new sentence-to-sentence semantic relatedness measure. The proposed measure optimized the word-to-word semantic relatedness that based on the depth of two concepts in WordNet. The study used Microsoft Research Paraphrases Corpus to validate the accuracy of the proposed method in identifying sentences with high semantic similarity. The result shows the proposed methods performed well compare to other unsupervised methods. At the end of the study, this paper also shows that the proposed semantic relatedness is able to identify relevant answers in Online Community Question Answering Services.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: semantic relatedness, sentences semantics, answer quality, paraphrase detection, online community question answering, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Mr. Jun Choi Lee
Date Deposited: 29 Aug 2016 20:05
Last Modified: 29 Aug 2016 20:05
URI: http://ir.unimas.my/id/eprint/12080

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