Abstract
Motivated by the large requirement of Web answer in E-learning, This this paper describes proposes a novel answer selection scheme for of NL-WASWebAnswer. designed for e-learning usersWith our scheme, the semantic types of the user’s question and the semantic templates were used to implement semantics-based answers selection. The semantic type is identified to reduce the retrieval scope firstly. of retrievalWhen the semantic type can’t be decided easily, the statistical similarity and the semantic similarity are computed to select the right answers. Otherwise, different strategies are proposed to match answers according as to the type of user’s question. If the semantic types between the user’s question and one candidate’s are same, the same parts of their semantic templates are compared. When they have correlative semantic types, the corresponding parts of their semantic templates are compared according to the rules that are used to match different templates. The experimental results show that NL-WAS can answer the most test questions correctly.
Funding for this work was provided by NSF grant 60103022 60373105 and 863 advanced tech. project grant 2001BA01A01. Xia Sun, PhD candidate. Qinghua Zheng, Professor. Committee member, Distance Education Technology Collaboration Committee, P.R.China. Committee member, Academy of Microcomputer, P.R.China.
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Sun, X., Zheng, Q. (2004). Semantics-Based Answers Selection in Question Answering System. In: Liu, W., Shi, Y., Li, Q. (eds) Advances in Web-Based Learning – ICWL 2004. ICWL 2004. Lecture Notes in Computer Science, vol 3143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27859-7_46
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DOI: https://doi.org/10.1007/978-3-540-27859-7_46
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