A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
The TREC question answering track
Natural Language Engineering
Finding semantically similar questions based on their answers
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Finding similar questions in large question and answer archives
Proceedings of the 14th ACM international conference on Information and knowledge management
An intelligent discussion-bot for answering student queries in threaded discussions
Proceedings of the 11th international conference on Intelligent user interfaces
Dependency structure language model for topic detection and tracking
Information Processing and Management: an International Journal
Recommending questions using the mdl-based tree cut model
Proceedings of the 17th international conference on World Wide Web
Finding question-answer pairs from online forums
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A classification-based approach to question answering in discussion boards
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
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Discussion boards and online forums provide a platform for users to share ideas, discuss issues and communicate with each other. Nowadays most of the discussion boards are used as problem-solving platforms which can be seen as question-answering knowledge bases. Therefore, if system can automatically locate the similar questions which have appeared previously, then the same answers could be returned to users to eliminate the time users wait for. In this paper, a novel question retrieval method is proposed. Keywords based inverted index is chosen as the basis technology, and dependency information, language model, and simple semantic information is used to extend it. Experimental results show the effectiveness and benefits of our approach.