CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
WordNet: a lexical database for English
Communications of the ACM
A maximum entropy approach to natural language processing
Computational Linguistics
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th 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
Exploiting redundancy in question answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Trainable question-answering systems
Trainable question-answering systems
A simple approach to building ensembles of Naive Bayesian classifiers for word sense disambiguation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Three heads are better than one
ANLC '94 Proceedings of the fourth conference on Applied natural language processing
Classifier combination for improved lexical disambiguation
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Answering what-is questions by Virtual Annotation
HLT '01 Proceedings of the first international conference on Human language technology research
Question answering using maximum entropy components
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
The structure and performance of an open-domain question answering system
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Sentence Fusion for Multidocument News Summarization
Computational Linguistics
HITIQA: towards analytical question answering
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Learning to identify single-snippet answers to definition questions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Handling biographical questions with implicature
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
An exploration of the principles underlying redundancy-based factoid question answering
ACM Transactions on Information Systems (TOIS)
A probabilistic graphical model for joint answer ranking in question answering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Hitiqa: High-quality intelligence through interactive question answering
Natural Language Engineering
Ranking community answers by modeling question-answer relationships via analogical reasoning
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Automatic selection of high quality parses created by a fully unsupervised parser
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
HITIQA: a data driven approach to interactive analytical question answering
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
A meta-learning approach for selecting between response automation strategies in a help-desk domain
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Cluster-based selection of statistical answering strategies
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Improving parsing accuracy by combining diverse dependency parsers
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
An empirical study of corpus-based response automation methods for an e-mail-based help-desk domain
Computational Linguistics
Graph-based answer fusion in multilingual question answering
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
Probabilistic models for answer-ranking in multilingual question-answering
ACM Transactions on Information Systems (TOIS)
Improving question answering by combining multiple systems via answer validation
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Information Processing and Management: an International Journal
Versatile question answering systems: seeing in synthesis
International Journal of Intelligent Information and Database Systems
Confidence driven unsupervised semantic parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning to select the correct answer in multi-stream question answering
Information Processing and Management: an International Journal
A multi-agent approach to question answering
PROPOR'06 Proceedings of the 7th international conference on Computational Processing of the Portuguese Language
An approach to answer selection in question-answering based on semantic relations
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Understanding script-based stories using commonsense reasoning
Cognitive Systems Research
Textual evidence gathering and analysis
IBM Journal of Research and Development
Sentence fusion for multidocument news summarization
Computational Linguistics
A phased ranking model for question answering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Motivated by the success of ensemble methods in machine learning and other areas of natural language processing, we developed a multi-strategy and multi-source approach to question answering which is based on combining the results from different answering agents searching for answers in multiple corpora. The answering agents adopt fundamentally different strategies, one utilizing primarily knowledge-based mechanisms and the other adopting statistical techniques. We present our multi-level answer resolution algorithm that combines results from the answering agents at the question, passage, and/or answer levels. Experiments evaluating the effectiveness of our answer resolution algorithm show a 35.0% relative improvement over our baseline system in the number of questions correctly answered, and a 32.8% improvement according to the average precision metric.