{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T11:17:52Z","timestamp":1777288672183,"version":"3.51.4"},"reference-count":32,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2005,3,1]],"date-time":"2005-03-01T00:00:00Z","timestamp":1109635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Transactions on Asian Language Information Processing"],"published-print":{"date-parts":[[2005,3]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.1145\/1066078.1066079","type":"journal-article","created":{"date-parts":[[2005,8,3]],"date-time":"2005-08-03T08:30:55Z","timestamp":1123057855000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":31,"title":["Domain-specific FAQ retrieval using independent aspects"],"prefix":"10.1145","volume":"4","author":[{"given":"Chung-Hsien","family":"Wu","sequence":"first","affiliation":[{"name":"National Cheng Kung University, Tainan, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jui-Feng","family":"Yeh","sequence":"additional","affiliation":[{"name":"National Cheng Kung University, Tainan, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming-Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"National Cheng Kung University, Tainan, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2005,3]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the Semantic Web Workshop 2002 at the 11th International World Wide Web Conference (WWW","author":"Ahmedi L.","year":"2002"},{"key":"e_1_2_1_2_1","volume-title":"Modern Information Retrieval","author":"Baeza-Yates R.","year":"1999"},{"key":"e_1_2_1_3_1","volume-title":"Proceedings of ACM SIGIR Conference. 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