-
Srihari, R.K.: Using speech input for image interpretation, annotation, and retrieval (1997)
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- Date
- 22. 9.1997 19:16:05
- Pages
- S.140-156
-
Lin, J.; Katz, B.: Building a reusable test collection for question answering (2006)
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- Abstract
- In contrast to traditional information retrieval systems, which return ranked lists of documents that users must manually browse through, a question answering system attempts to directly answer natural language questions posed by the user. Although such systems possess language-processing capabilities, they still rely on traditional document retrieval techniques to generate an initial candidate set of documents. In this article, the authors argue that document retrieval for question answering represents a task different from retrieving documents in response to more general retrospective information needs. Thus, to guide future system development, specialized question answering test collections must be constructed. They show that the current evaluation resources have major shortcomings; to remedy the situation, they have manually created a small, reusable question answering test collection for research purposes. In this article they describe their methodology for building this test collection and discuss issues they encountered regarding the notion of "answer correctness."
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- Journal of the American Society for Information Science and Technology. 57(2006) no.7, S.851-861
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Kneedler, W.H.; Sizemore, E.J.: Speech synthesis + online library catalog = "talking catalog" (1993)
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Voorhees, E.M.: Question answering in TREC (2005)
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Keller, F.: How do humans deal with ungrammatical input? : Experimental evidence and computational modelling (1996)
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Marx, J.: ¬Die '¬Computer-Talk-These' in der Sprachgenerierung : Hinweise zur Gestaltung natürlichsprachlicher Zustandsanzeigen in multimodalen Informationssystemen (1996)
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Schultz, T.; Soltau, H.: Automatische Identifizierung spontan gesprochener Sprachen mit neuronalen Netzen (1996)
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Hannabuss, S.: Dialogue and the search for information (1989)
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Sparck Jones, K.; Jones, G.J.F.; Foote, J.T.; Young, S.J.: Experiments in spoken document retrieval (1996)
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- Footnote
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Thompson, L.A.; Ogden, W.C.: Visible speech improves human language understanding : implications for speech processing systems (1995)
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Burke, R.D.: Question answering from frequently asked question files : experiences with the FAQ Finder System (1997)
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Schneider, R.: Question answering : das Retrieval der Zukunft? (2007)
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Nhongkai, S.N.; Bentz, H.-J.: Bilinguale Suche mittels Konzeptnetzen (2006)
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Pomerantz, J.: ¬A linguistic analysis of question taxonomies (2005)
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Tartakovski, O.; Shramko, M.: Implementierung eines Werkzeugs zur Sprachidentifikation in mono- und multilingualen Texten (2006)
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Young, C.W.; Eastman, C.M.; Oakman, R.L.: ¬An analysis of ill-formed input in natural language queries to document retrieval systems (1991)
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Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002)
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Galitsky, B.: Can many agents answer questions better than one? (2005)
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- Abstract
- The paper addresses the issue of how online natural language question answering, based on deep semantic analysis, may compete with currently popular keyword search, open domain information retrieval systems, covering a horizontal domain. We suggest the multiagent question answering approach, where each domain is represented by an agent which tries to answer questions taking into account its specific knowledge. The meta-agent controls the cooperation between question answering agents and chooses the most relevant answer(s). We argue that multiagent question answering is optimal in terms of access to business and financial knowledge, flexibility in query phrasing, and efficiency and usability of advice. The knowledge and advice encoded in the system are initially prepared by domain experts. We analyze the commercial application of multiagent question answering and the robustness of the meta-agent. The paper suggests that a multiagent architecture is optimal when a real world question answering domain combines a number of vertical ones to form a horizontal domain.
