Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
MURAX: a robust linguistic approach for question answering using an on-line encyclopedia
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Question-answering by predictive annotation
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Extended Boolean information retrieval
Communications of the ACM
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Extending the boolean and vector space models of information retrieval with p-norm queries and multiple concept types
Importance of pronominal anaphora resolution in question answering systems
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Answer Extraction in Technical Domains
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Multilingual question answering with high portability on relational databases
MultiSumQA '02 proceedings of the 2002 conference on multilingual summarization and question answering - Volume 19
A reliable indexing method for a practical QA system
MultiSumQA '02 proceedings of the 2002 conference on multilingual summarization and question answering - Volume 19
Expertise Analysis in a Question Answer Portal for Author Ranking
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
QUESTION ANSWERING USING QUESTION CLASSIFICATION AND DOCUMENT TAGGING
Applied Artificial Intelligence
Topic indexing and retrieval for factoid QA
IRQA '08 Coling 2008: Proceedings of the 2nd workshop on Information Retrieval for Question Answering
A spoken question answering system based on conditional knowledge
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume I
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We propose a Question-answering (QA) system in Korean that uses a predictive answer indexer. The predictive answer indexer, first, extracts all answer candidates in a document in indexing time. Then, it gives scores to the adjacent content words that are closely related with each answer candidate. Next, it stores the weighted content words with each candidate into a database. Using this technique, along with a complementary analysis of questions, the proposed QA system can save response time because it is not necessary for the QA system to extract answer candidates with scores on retrieval time. If the QA system is combined with a traditional Information Retrieval system, it can improve the document retrieval precision for closed-class questions after minimum loss of retrieval time.