A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
C4.5: programs for machine learning
C4.5: programs for machine learning
High performance question/answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
On the MSE robustness of batching estimators
Proceedings of the 33nd conference on Winter simulation
Structured use of external knowledge for event-based open domain question answering
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Using knowledge to facilitate factoid answer pinpointing
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Producing biographical summaries: combining linguistic knowledge with corpus statistics
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
In question answering, two heads are better than one
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
COGEX: a logic prover for question answering
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Offline strategies for online question answering: answering questions before they are asked
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A noisy-channel approach to question answering
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The structure and performance of an open-domain question answering system
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Automatic question answering using the web: Beyond the Factoid
Information Retrieval
Splitting complex temporal questions for question answering systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Question answering using constraint satisfaction: QA-by-Dossier-with-Constraints
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Multi-field information extraction and cross-document fusion
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Journal of Computing Sciences in Colleges
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Traditional question answering systems adopt the following framework: parsing questions, searching for relevant documents, and identifying/generating answers. However, this framework does not work well for questions with hidden assumptions and implicatures. In this paper, we describe a novel idea, a cascading guidance strategy, which can not only identify potential traps in questions but further guide the answer extraction procedure by recognizing whether there are multiple answers for a question. This is the first attempt to solve implicature problem for complex QA in a cascading fashion using N-gram language models as features. We here investigate questions with implicatures related to biography facts in a web-based QA system, Power-Bio. We compare the performances of Decision Tree, Naïve Bayes, SVM (Support Vector Machine), and ME (Maximum Entropy) classification methods. The integration of the cascading guidance strategy can help extract answers for questions with implicatures and produce satisfactory results in our experiments.