Search (26 results, page 1 of 2)

  • × theme_ss:"Sprachretrieval"
  1. Sparck Jones, K.; Jones, G.J.F.; Foote, J.T.; Young, S.J.: Experiments in spoken document retrieval (1996) 0.02
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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
    Footnote
    Wiederabdruck in: Readings in informatio retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.493-502.
    Source
    Information processing and management. 32(1996) no.4, S.399-417
    Type
    a
  2. Strötgen, R.; Mandl, T.; Schneider, R.: Entwicklung und Evaluierung eines Question Answering Systems im Rahmen des Cross Language Evaluation Forum (CLEF) (2006) 0.02
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    Pages
    S.223-234
    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
    Type
    a
  3. Tartakovski, O.; Shramko, M.: Implementierung eines Werkzeugs zur Sprachidentifikation in mono- und multilingualen Texten (2006) 0.01
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    Pages
    S.171-182
    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
    Type
    a
  4. Schneider, R.: Question answering : das Retrieval der Zukunft? (2007) 0.01
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    Source
    Zeitschrift für Bibliothekswesen und Bibliographie. 54(2007) H.1, S.3-11
    Type
    a
  5. Nhongkai, S.N.; Bentz, H.-J.: Bilinguale Suche mittels Konzeptnetzen (2006) 0.01
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    Pages
    S.203-222
    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
    Type
    a
  6. Kruschwitz, U.; AI-Bakour, H.: Users want more sophisticated search assistants : results of a task-based evaluation (2005) 0.01
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    Abstract
    The Web provides a massive knowledge source, as do intranets and other electronic document collections. However, much of that knowledge is encoded implicitly and cannot be applied directly without processing into some more appropriate structures. Searching, browsing, question answering, for example, could all benefit from domain-specific knowledge contained in the documents, and in applications such as simple search we do not actually need very "deep" knowledge structures such as ontologies, but we can get a long way with a model of the domain that consists of term hierarchies. We combine domain knowledge automatically acquired by exploiting the documents' markup structure with knowledge extracted an the fly to assist a user with ad hoc search requests. Such a search system can suggest query modification options derived from the actual data and thus guide a user through the space of documents. This article gives a detailed account of a task-based evaluation that compares a search system that uses the outlined domain knowledge with a standard search system. We found that users do use the query modification suggestions proposed by the system. The main conclusion we can draw from this evaluation, however, is that users prefer a system that can suggest query modifications over a standard search engine, which simply presents a ranked list of documents. Most interestingly, we observe this user preference despite the fact that the baseline system even performs slightly better under certain criteria.
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.13, S.1377-1393
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
    Type
    a
  7. Srihari, R.K.: Using speech input for image interpretation, annotation, and retrieval (1997) 0.01
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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
    Pages
    S.140-156
    Source
    Digital image access and retrieval: Proceedings of the 1996 Clinic on Library Applications of Data Processing, 24-26 Mar 1996. Ed.: P.B. Heidorn u. B. Sandore
    Type
    a
  8. Voorhees, E.M.: Question answering in TREC (2005) 0.01
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    Pages
    S.233-259
    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
    Type
    a
  9. Jensen, N.: Evaluierung von mehrsprachigem Web-Retrieval : Experimente mit dem EuroGOV-Korpus im Rahmen des Cross Language Evaluation Forum (CLEF) (2006) 0.01
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    Pages
    S.235-244
    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
    Type
    a
  10. Schultz, T.; Soltau, H.: Automatische Identifizierung spontan gesprochener Sprachen mit neuronalen Netzen (1996) 0.01
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    Pages
    S.102-110
    Type
    a
  11. Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002) 0.00
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    Abstract
    Answering open-domain factual questions requires Natural Language processing for refining document selection and answer identification. With our system QALC, we have participated in the Question Answering track of the TREC8, TREC9 and TREC10 evaluations. QALC performs an analysis of documents relying an multiword term searches and their linguistic variation both to minimize the number of documents selected and to provide additional clues when comparing question and sentence representations. This comparison process also makes use of the results of a syntactic parsing of the questions and Named Entity recognition functionalities. Answer extraction relies an the application of syntactic patterns chosen according to the kind of information that is sought, and categorized depending an the syntactic form of the question. These patterns allow QALC to handle nicely linguistic variations at the answer level.
    Source
    Knowledge organization. 29(2002) nos.3/4, S.135-155
    Type
    a
  12. Radev, D.; Fan, W.; Qu, H.; Wu, H.; Grewal, A.: Probabilistic question answering on the Web (2005) 0.00
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    Abstract
    Web-based search engines such as Google and NorthernLight return documents that are relevant to a user query, not answers to user questions. We have developed an architecture that augments existing search engines so that they support natural language question answering. The process entails five steps: query modulation, document retrieval, passage extraction, phrase extraction, and answer ranking. In this article, we describe some probabilistic approaches to the last three of these stages. We show how our techniques apply to a number of existing search engines, and we also present results contrasting three different methods for question answering. Our algorithm, probabilistic phrase reranking (PPR), uses proximity and question type features and achieves a total reciprocal document rank of .20 an the TREC8 corpus. Our techniques have been implemented as a Web-accessible system, called NSIR.
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.6, S.571-583
    Type
    a
  13. Peters, B.F.: Online searching using speech as a man / machine interface (1989) 0.00
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    Source
    Information processing and management. 25(1989), S.391-406
    Type
    a
  14. Kneedler, W.H.; Sizemore, E.J.: Speech synthesis + online library catalog = "talking catalog" (1993) 0.00
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    Source
    Library hi tech. 11(1993) no.1, S.57-65
    Type
    a
  15. Rösener, C.: ¬Die Stecknadel im Heuhaufen : Natürlichsprachlicher Zugang zu Volltextdatenbanken (2005) 0.00
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    Content
    5: Interaktion 5.1 Frage-Antwort- bzw. Dialogsysteme: Forschungen und Projekte 5.2 Darstellung und Visualisierung von Wissen 5.3 Das Dialogsystem im Rahmen des LeWi-Projektes 5.4 Ergebnisdarstellung und Antwortpräsentation im LeWi-Kontext 6: Testumgebungen und -ergebnisse 7: Ergebnisse und Ausblick 7.1 Ausgangssituation 7.2 Schlussfolgerungen 7.3 Ausblick Anhang A Auszüge aus der Grob- bzw. Feinklassifikation des BMM Anhang B MPRO - Formale Beschreibung der wichtigsten Merkmale ... Anhang C Fragentypologie mit Beispielsätzen (Auszug) Anhang D Semantische Merkmale im morphologischen Lexikon (Auszug) Anhang E Regelbeispiele für die Fragentypzuweisung Anhang F Aufstellung der möglichen Suchen im LeWi-Dialogmodul (Auszug) Anhang G Vollständiger Dialogbaum zu Beginn des Projektes Anhang H Statuszustände zur Ermittlung der Folgefragen (Auszug)
    Pages
    X,243 S
  16. Burke, R.D.: Question answering from frequently asked question files : experiences with the FAQ Finder System (1997) 0.00
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    Abstract
    Describes FAQ Finder, a natural language question-answering system that uses files of frequently asked questions as its knowledge base. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, FAQ Finder uses a semantic knowledge base (Wordnet) to improve its ability to match question and answer. Includes results from an evaluation of the system's performance and shows that a combination of semantic and statistical techniques works better than any single approach
    Source
    AI magazine. 18(1997) no.2, S.57-66
    Type
    a
  17. Pomerantz, J.: ¬A linguistic analysis of question taxonomies (2005) 0.00
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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.
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.715-728
    Type
    a
  18. Thompson, L.A.; Ogden, W.C.: Visible speech improves human language understanding : implications for speech processing systems (1995) 0.00
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    Abstract
    Presents evidence from the study of human language understanding suggesting that the ability to perceive visible speech can greatly influence the ability to understand and remember spoken language. A view of the speaker's face can greatly aid in the perception of ambiguous or noisy speech and can aid cognitive processing of speech leading to better understanding and recall. Some of these effects have been replaced using computer synthesized visual and auditory speech. When giving an interface a voice, it may be best to give it a face too
    Source
    Artificial intelligence review. 9(1995) nos.4/5, S.347-358
    Type
    a
  19. Keller, F.: How do humans deal with ungrammatical input? : Experimental evidence and computational modelling (1996) 0.00
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    Pages
    S.27-34
    Type
    a
  20. Marx, J.: ¬Die '¬Computer-Talk-These' in der Sprachgenerierung : Hinweise zur Gestaltung natürlichsprachlicher Zustandsanzeigen in multimodalen Informationssystemen (1996) 0.00
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