An approach to natural language for document retrieval
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation and information retrieval
SIGIR '94 Proceedings of the 17th 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
Searching XML documents via XML fragments
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Semantic indexing using WordNet senses
RANLPIR '00 Proceedings of the ACL-2000 workshop on Recent advances in natural language processing and information retrieval: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 11
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Semantic search via XML fragments: a high-precision approach to IR
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Dependency tree kernels for relation extraction
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Extracting relations with integrated information using kernel methods
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Factorizing complex models: a case study in mention detection
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Integrating linguistic knowledge in passage retrieval for question answering
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Language modelization and categorization for voice-activated QA
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Collaboratively built semi-structured content and Artificial Intelligence: The story so far
Artificial Intelligence
Repeatable and reliable semantic search evaluation
Web Semantics: Science, Services and Agents on the World Wide Web
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Researchers have shown that various natural language processing techniques can be used in document analysis to impact search performance. For the most part, they examined how an analysis system with certain performance characteristics can be leveraged to improve document and/or passage search results. We have previously shown that semantic queries which utilize named entity and relation information extracted from the corpus can lead to significant improvement in search performance. In this paper, we extend our previous efforts and examine how search performance degrades in the face of imperfect named entity and relation extraction. Our study was carried out by developing gold standard annotated corpora and applying different error models to the gold standard annotations to simulate errors made by automatic recognizers. We identify automatic recognizer characteristics that make them more amenable to our search tasks, show that recognizer recall has more significant impact on semantic search performance than its precision, and demonstrate that significant improvement in both MAP and Exact Precision scores can be achieved by adopting automatic named entity and relation recognizers with near state-of-the-art performance.