Abstract
Semantic similarity plays a significant role in the areas of Web mining, information retrieval, NLP, and text mining. Even though it is exploited in various applications, accurately measuring semantic similarity still remains a challenging task. The online question answer portal is an important application of natural language processing. Accuracy of answers is a critical issue in these types of portals and has attracted the attention of many researchers. In this paper a method that uses the semantic similarity measure is proposed to calculate the similarity between the user’s answer with the stored answer in a question answer database. The main focus here is to improve the similarity of the user’s answer with the stored answer. For experimental purposes a set of questions and their answers has been taken. The user’s answers have been stored by taking the inputs from the random user and then this answer is compared with the stored answers. The experimental results show that the proposed method is performing better than the existing methods.
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Shashank, Sukhbir Kaur, Shailendra Singh (2016). Improving Accuracy of Answer Checking in Online Question Answer Portal Using Semantic Similarity Measure. In: Shetty, N., Prasad, N., Nalini, N. (eds) Emerging Research in Computing, Information, Communication and Applications . Springer, Singapore. https://doi.org/10.1007/978-981-10-0287-8_23
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DOI: https://doi.org/10.1007/978-981-10-0287-8_23
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