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Srihari, R.K.: Using speech input for image interpretation, annotation, and retrieval (1997)
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- Abstract
- Explores the interaction of textual and photographic information in an integrated text and image database environment and describes 3 different applications involving the exploitation of linguistic context in vision. Describes the practical application of these ideas in working systems. PICTION uses captions to identify human faces in a photograph, wile Show&Tell is a multimedia system for semi automatic image annotation. The system combines advances in speech recognition, natural language processing and image understanding to assist in image annotation and enhance image retrieval capabilities. Presents an extension of this work to video annotation and retrieval
- Date
- 22. 9.1997 19:16:05
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Strötgen, R.; Mandl, T.; Schneider, R.: Entwicklung und Evaluierung eines Question Answering Systems im Rahmen des Cross Language Evaluation Forum (CLEF) (2006)
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- Abstract
- Question Answering Systeme versuchen, zu konkreten Fragen eine korrekte Antwort zu liefern. Dazu durchsuchen sie einen Dokumentenbestand und extrahieren einen Bruchteil eines Dokuments. Dieser Beitrag beschreibt die Entwicklung eines modularen Systems zum multilingualen Question Answering. Die Strategie bei der Entwicklung zielte auf eine schnellstmögliche Verwendbarkeit eines modularen Systems, das auf viele frei verfügbare Ressourcen zugreift. Das System integriert Module zur Erkennung von Eigennamen, zu Indexierung und Retrieval, elektronische Wörterbücher, Online-Übersetzungswerkzeuge sowie Textkorpora zu Trainings- und Testzwecken und implementiert eigene Ansätze zu den Bereichen der Frage- und AntwortTaxonomien, zum Passagenretrieval und zum Ranking alternativer Antworten.
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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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Thompson, L.A.; Ogden, W.C.: Visible speech improves human language understanding : implications for speech processing systems (1995)
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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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- Abstract
- Describes experiments in the retrieval of spoken documents in multimedia systems. Speech documents pose a particular problem for retrieval since their words as well as contents are unknown. Addresses this problem, for a video mail application, by combining state of the art speech recognition with established document retrieval technologies so as to provide an effective and efficient retrieval tool. Tests with a small spoken message collection show that retrieval precision for the spoken file can reach 90% of that obtained when the same file is used, as a benchmark, in text transcription form
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Pomerantz, J.: ¬A linguistic analysis of question taxonomies (2005)
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- Abstract
- Recent work in automatic question answering has called for question taxonomies as a critical component of the process of machine understanding of questions. There is a long tradition of classifying questions in library reference services, and digital reference services have a strong need for automation to support scalability. Digital reference and question answering systems have the potential to arrive at a highly fruitful symbiosis. To move towards this goal, an extensive review was conducted of bodies of literature from several fields that deal with questions, to identify question taxonomies that exist in these bodies of literature. In the course of this review, five question taxonomies were identified, at four levels of linguistic analysis.
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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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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.
