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|Title:||Effectiveness of Web page classification on finding list answers||Authors:||Yang, H.
Web page classification
|Issue Date:||2004||Citation:||Yang, H.,Chua, T.-S. (2004). Effectiveness of Web page classification on finding list answers. Proceedings of Sheffield SIGIR - Twenty-Seventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval : 522-523. ScholarBank@NUS Repository.||Abstract:||List question answering (QA) offers a unique challenge in effectively and efficiently locating a complete set of distinct answers from huge corpora or the Web. In TREC-12, the median average F performance of list QA systems was only 6.9%. This paper exploits the wealth of freely available text and link structures on the Web to seek complete answers to list questions. We employ natural language parsing, web page classification and clustering to find reliable list answers. We also study the effectiveness of web page classification on both the recall and uniqueness of answers for web-based list QA.||Source Title:||Proceedings of Sheffield SIGIR - Twenty-Seventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval||URI:||http://scholarbank.nus.edu.sg/handle/10635/42196||ISBN:||1581138814|
|Appears in Collections:||Staff Publications|
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