Domain-specific FAQ retrieval using independent aspects

Chung Hsien Wu, Jui Feng Yeh, Ming Jun Chen

研究成果: Article

33 引文 斯高帕斯(Scopus)

摘要

This investigation presents an approach to domain-specific FAQ (frequently-asked question) retrieval using independent aspects. The data analysis classifies the questions in the collected QA (question-answer) pairs into ten question types in accordance with question stems. The answers in the QA pairs are then paragraphed and clustered using latent semantic analysis and the K-means algorithm. For semantic representation of the aspects, a domain-specific ontology is constructed based on WordNet and HowNet. A probabilistic mixture model is then used to interpret the query and QA pairs based on independent aspects; hence the retrieval process can be viewed as the maximum likelihood estimation problem. The expectation-maximization (EM) algorithm is employed to estimate the optimal mixing weights in the probabilistic mixture model. Experimental results indicate that the proposed approach outperformed the FAQ-Finder system in medical FAQ retrieval.

原文English
頁(從 - 到)1-17
頁數17
期刊ACM Transactions on Asian Language Information Processing
4
發行號1
DOIs
出版狀態Published - 2005 三月 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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