QuASM: a system for question answering using semi-structured data
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Performance issues and error analysis in an open-domain question answering system
ACM Transactions on Information Systems (TOIS)
Toward semantics-based answer pinpointing
HLT '01 Proceedings of the first international conference on Human language technology research
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Question classification with support vector machines and error correcting codes
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Parsing and question classification for question answering
ODQA '01 Proceedings of the workshop on Open-domain question answering - Volume 12
Building a reusable test collection for question answering
Journal of the American Society for Information Science and Technology - Research Articles
Learning question classifiers: the role of semantic information
Natural Language Engineering
A language independent method for question classification
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Lexical validation of answers in Question Answering
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Question classification using head words and their hypernyms
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Subtree mining for question classification problem
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Automatic answer validation using COGEX
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Improving subtree-based question classification classifiers with word-cluster models
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
A support vector machine-based context-ranking model for question answering
Information Sciences: an International Journal
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Question Answering Systems, unlike search engines, are providing answers to the users' questions in succinct form which requires the prior knowledge of the expectation of the user. Question classification module of a Question Answering System plays a very important role in determining the expectations of the user. In the literature, incorrect question classification has been cited as one of the major factors for the poor performance of the Question Answering Systems and this emphasizes on the importance of question classification module designing. In this article, we have proposed a question classification method that exploits the powerful semantic features of the WordNet and the vast knowledge repository of the Wikipedia to describe informative terms explicitly. We have trained our system over a standard set of 5500 questions (by UIUC) and then tested it over five TREC question collections. We have compared our results with some standard results reported in the literature and observed a significant improvement in the accuracy of question classification. The question classification accuracy suggests the effectiveness of the method which is promising in the field of open-domain question classification. Judging the correctness of the answer is an important issue in the field of question answering. In this article, we are extending question classification as one of the heuristics for answer validation. We are proposing a World Wide Web based solution for answer validation where answers returned by open-domain Question Answering Systems can be validated using online resources such as Wikipedia and Google. We have applied several heuristics for answer validation task and tested them against some popular web based open-domain Question Answering Systems over a collection of 500 questions collected from standard sources such as TREC, the Worldbook, and the Worldfactbook. The proposed method seems to be promising for automatic answer validation task.