A Novel Composite Kernel and Application to Question Retrieval
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Question retrieval plays important role in question and answering systems. The main problem is how to measure the similarity between candidate questions and query question. This paper presents a tree kernel based method, named weighted tree kernel, to calculate the similarity of sentences' structures and proposes improvements to the original tree kernel algorithm. In order to reduce the effect on tree kernel bringing by syntactic parsing, a composite kernel is proposed based on the weighted tree kernel and two other string kernels, which can capture syntax, part-of-speech and lexical level information of a sentence, to calculate the semantic similarity between question sentences. Experimental results on Yahoo! Answers dataset show that the proposed method outperforms traditional vector space model based methods by 24.02% in question retrieval accuracy.
author list (cited authors)
Wang, J., Li, Z., Hu, X., & Hu, B.