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  • × year_i:[2000 TO 2010}
  1. Hawking, D.; Robertson, S.: On collection size and retrieval effectiveness (2003) 0.14 
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    Date
    14. 8.2005 14:22:22
    Source
    Information retrieval. 6(2003) no.1, S.99-150
  2. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.10 
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  3. Enser, P.G.B.: Visual image retrieval (2008) 0.10 
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    Date
    22. 1.2012 13:01:26
  4. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.09 
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    Abstract
    By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.
    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  5. Denda, K.: Beyond subject headings : a structured information retrieval tool for interdisciplinary fields (2005) 0.09 
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    Date
    10. 9.2000 17:38:22
  6. Voorhees, E.M.; Harman, D.: Overview of the Sixth Text REtrieval Conference (TREC-6) (2000) 0.09 
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    Date
    11. 8.2001 16:22:19
  7. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.08 
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  8. Lim, E.: Southeast Asian subject gateways : an examination of their classification practices (2000) 0.07 
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    Date
    22. 6.2002 19:42:47
    Theme
    Klassifikationssysteme im Online-Retrieval
  9. Zhang, L.; Pan, Y.; Zhang, T.: Focused named entity recognition using machine learning (2004) 0.07 
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    Date
    15.10.2005 19:57:22
    Source
    SIGIR'04: Proceedings of the 27th Annual International ACM-SIGIR Conference an Research and Development in Information Retrieval. Ed.: K. Järvelin, u.a
  10. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.06 
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    Abstract
    We propose a novel approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. The ability of the logic to handle expressive representations along with the use of such classical notions are promising characteristics for IR systems. The approach proposed here has been efficiently implemented and experiments against test collections are presented.
    Date
    22. 3.2003 19:27:23
    Footnote
    Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
  11. ¬The Eleventh Text Retrieval Conference, TREC 2002 (2003) 0.06 
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    Abstract
    Proceedings of the llth TREC-conference held in Gaithersburg, Maryland (USA), November 19-22, 2002. Aim of the conference was discussion an retrieval and related information-seeking tasks for large test collection. 93 research groups used different techniques, for information retrieval from the same large database. This procedure makes it possible to compare the results. The tasks are: Cross-language searching, filtering, interactive searching, searching for novelty, question answering, searching for video shots, and Web searching.
  12. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.06 
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    Date
    22. 8.2009 12:54:24
    Theme
    Klassifikationssysteme im Online-Retrieval
  13. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.06 
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    Abstract
    A new search paradigm, in which the primary user activity is the guided exploration of a complex information space rather than the retrieval of items based on precise specifications, is proposed. The author claims that this paradigm is the norm in most practical applications, and that solutions based on traditional search methods are not effective in this context. He then presents a solution based on dynamic taxonomies, a knowledge management model that effectively guides users to reach their goal while giving them total freedom in exploring the information base. Applications, benefits, and current research are discussed.
    Date
    22. 7.2006 17:56:22
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  14. Mittler, E.; Schulz, M.: ProPrint world-wide print-on-demand services for study and research (2004) 0.06 
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    Abstract
    The libraries of more and more universities and research institutions have local digital repositories, and the amount of material is increasing every day. Users need an integrated retrieval interface that allows aggregated searching across multiple document servers without having to resort to manual processes. ProPrint offers an on-demand print service within Germany for over 2,000 monographs and 1,000 journals. Partners worldwide are now invited to join.
    Date
    8.10.2004 14:22:14
    Source
    Library hi tech. 22(2004) no.2, S.227-230
  15. Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003) 0.06 
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    Abstract
    Research an the use of mathematical, logical, and formal methods, has been central to Information Retrieval research for a long time. Research in this area is important not only because it helps enhancing retrieval effectiveness, but also because it helps clarifying the underlying concepts of Information Retrieval. In this article we outline some of the major aspects of the subject, and summarize the papers of this special issue with respect to how they relate to these aspects. We conclude by highlighting some directions of future research, which are needed to better understand the formal characteristics of Information Retrieval.
    Date
    22. 3.2003 19:27:36
    Footnote
    Einführung zu den Beiträgen eines Themenheftes: Mathematical, logical, and formal methods in information retrieval
  16. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.06 
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    Abstract
    In this paper methods for both speeding up passage processing and examining more passages using parallel computers are explored. The number of passages processed are varied in order to examine the effect on retrieval effectiveness and efficiency. The particular algorithm applied has previously been used to good effect in Okapi experiments at TREC. This algorithm and the mechanism for applying parallel computing to speed up processing are described.
    Date
    20. 1.2007 18:30:22
  17. Peereboom, M.: DutchESS : Dutch Electronic Subject Service - a Dutch national collaborative effort (2000) 0.06 
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    Abstract
    This article gives an overview of the design and organisation of DutchESS, a Dutch information subject gateway created as a national collaborative effort of the National Library and a number of academic libraries. The combined centralised and distributed model of DutchESS is discussed, as well as its selection policy, its metadata format, classification scheme and retrieval options. Also some options for future collaboration on an international level are explored
    Date
    22. 6.2002 19:39:23
    Theme
    Klassifikationssysteme im Online-Retrieval
  18. Trotman, A.: Searching structured documents (2004) 0.06 
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    Abstract
    Structured document interchange formats such as XML and SGML are ubiquitous, however, information retrieval systems supporting structured searching are not. Structured searching can result in increased precision. A search for the author "Smith" in an unstructured corpus of documents specializing in iron-working could have a lower precision than a structured search for "Smith as author" in the same corpus. Analysis of XML retrieval languages identifies additional functionality that must be supported including searching at, and broken across multiple nodes in the document tree. A data structure is developed to support structured document searching. Application of this structure to information retrieval is then demonstrated. Document ranking is examined and adapted specifically for structured searching.
    Date
    14. 8.2004 10:39:22
  19. Schrodt, R.: Tiefen und Untiefen im wissenschaftlichen Sprachgebrauch (2008) 0.06 
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    Content
    Vgl. auch: https://studylibde.com/doc/13053640/richard-schrodt. Vgl. auch: http%3A%2F%2Fwww.univie.ac.at%2FGermanistik%2Fschrodt%2Fvorlesung%2Fwissenschaftssprache.doc&usg=AOvVaw1lDLDR6NFf1W0-oC9mEUJf.
  20. Crestani, F.; Du, H.: Written versus spoken queries : a qualitative and quantitative comparative analysis (2006) 0.05 
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    Abstract
    The authors report on an experimental study on the differences between spoken and written queries. A set of written and spontaneous spoken queries are generated by users from written topics. These two sets of queries are compared in qualitative terms and in terms of their retrieval effectiveness. Written and spoken queries are compared in terms of length, duration, and part of speech. In addition, assuming perfect transcription of the spoken queries, written and spoken queries are compared in terms of their aptitude to describe relevant documents. The retrieval effectiveness of spoken and written queries is compared using three different information retrieval models. The results show that using speech to formulate one's information need provides a way to express it more naturally and encourages the formulation of longer queries. Despite that, longer spoken queries do not seem to significantly improve retrieval effectiveness compared with written queries.
    Date
    5. 6.2006 11:22:23

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