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  • × theme_ss:"Retrievalalgorithmen"
  1. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.02
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    Abstract
    This book offers a comprehensive and consistent mathematical approach to information retrieval (IR) without which no implementation is possible, and sheds an entirely new light upon the structure of IR models. It contains the descriptions of all IR models in a unified formal style and language, along with examples for each, thus offering a comprehensive overview of them. The book also creates mathematical foundations and a consistent mathematical theory (including all mathematical results achieved so far) of IR as a stand-alone mathematical discipline, which thus can be read and taught independently. Also, the book contains all necessary mathematical knowledge on which IR relies, to help the reader avoid searching different sources. The book will be of interest to computer or information scientists, librarians, mathematicians, undergraduate students and researchers whose work involves information retrieval.
    Date
    22. 3.2008 12:26:32
    Series
    Mathematical modelling: theory and applications; 12
  2. Baloh, P.; Desouza, K.C.; Hackney, R.: Contextualizing organizational interventions of knowledge management systems : a design science perspectiveA domain analysis (2012) 0.02
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    Abstract
    We address how individuals' (workers) knowledge needs influence the design of knowledge management systems (KMS), enabling knowledge creation and utilization. It is evident that KMS technologies and activities are indiscriminately deployed in most organizations with little regard to the actual context of their adoption. Moreover, it is apparent that the extant literature pertaining to knowledge management projects is frequently deficient in identifying the variety of factors indicative for successful KMS. This presents an obvious business practice and research gap that requires a critical analysis of the necessary intervention that will actually improve how workers can leverage and form organization-wide knowledge. This research involved an extensive review of the literature, a grounded theory methodological approach and rigorous data collection and synthesis through an empirical case analysis (Parsons Brinckerhoff and Samsung). The contribution of this study is the formulation of a model for designing KMS based upon the design science paradigm, which aspires to create artifacts that are interdependent of people and organizations. The essential proposition is that KMS design and implementation must be contextualized in relation to knowledge needs and that these will differ for various organizational settings. The findings present valuable insights and further understanding of the way in which KMS design efforts should be focused.
    Date
    11. 6.2012 14:22:34
  3. Sachs, W.M.: ¬An approach to associative retrieval through the theory of fuzzy sets (1976) 0.01
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    Abstract
    The theory of fuzzy sets is used to provide a rogorous formulation of the problem of associative retrieval. This formulation suggests the idea of using fuzzy clustering to organize data for retrieval
  4. Srinivasan, P.: Intelligent information retrieval using rough set approximations (1989) 0.01
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    Abstract
    The theory of rough sets was introduced in 1982. It allows the classification of objects into sets of equivalent members based on their attributes. Any combination of the same objetcts (or even their attributes) may be examined using the resultant classification. The theory has direct applications in the design and evaluation of classification schemes and the selection of discriminating attributes. Introductory papers discuss its application in the domain of medical diagnostic systems and the design of information retrieval systems accessing collections of documents. Advantages offered by the theory are: the implicit inclusion of Boolean logic; term weighting; and the ability to rank retrieved documents.
  5. White, H. D.: Co-cited author retrieval and relevance theory : examples from the humanities (2015) 0.01
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  6. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.01
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  7. Archuby, C.G.: Interfaces se recuperacion para catalogos en linea con salidas ordenadas por probable relevancia (2000) 0.01
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    Date
    29. 1.1996 18:23:13
    Source
    Ciencia da informacao. 29(2000) no.3, S.5-13
  8. Crestani, F.: Combination of similarity measures for effective spoken document retrieval (2003) 0.01
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    Source
    Journal of information science. 29(2003) no.2, S.87-96
  9. Sparck Jones, K.: IDF term weighting and IR research lessons (2004) 0.01
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    Abstract
    Robertson comments on the theoretical status of IDF term weighting. Its history illustrates how ideas develop in a specific research context, in theory/experiment interaction, and in operational practice.
  10. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.01
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    Date
    30. 3.2001 13:32:22
  11. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.01
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    Date
    25. 8.2005 17:42:22
  12. Lalmas, M.; Ruthven, I.: Representing and retrieving structured documents using the Dempster-Shafer theory of evidence : modelling and evaluation (1998) 0.01
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    Abstract
    Reports on a theoretical model of structured document indexing and retrieval based on the Dempster-Schafer Theory of Evidence. Includes a description of the model of structured document retrieval, the representation of structured documents, the representation of individual components, how components are combined, details of the combination process, and how relevance is captured within the model. Also presents a detailed account of an implementation of the model, and an evaluation scheme designed to test the effectiveness of the model
  13. Robertson, S.: Understanding inverse document frequency : on theoretical arguments for IDF (2004) 0.01
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    Abstract
    The term-weighting function known as IDF was proposed in 1972, and has since been extremely widely used, usually as part of a TF*IDF function. It is often described as a heuristic, and many papers have been written (some based on Shannon's Information Theory) seeking to establish some theoretical basis for it. Some of these attempts are reviewed, and it is shown that the Information Theory approaches are problematic, but that there are good theoretical justifications of both IDF and TF*IDF in the traditional probabilistic model of information retrieval.
  14. Okada, M.; Ando, K.; Lee, S.S.; Hayashi, Y.; Aoe, J.I.: ¬An efficient substring search method by using delayed keyword extraction (2001) 0.01
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    Date
    29. 3.2002 17:24:03
  15. Cole, C.: Intelligent information retrieval: diagnosing information need : Part II: uncertainty expansion in a prototype of a diagnostic IR tool (1998) 0.01
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    Date
    11. 8.2001 14:48:29
  16. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.01
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    Date
    14. 6.2015 22:12:44
  17. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.01
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    Date
    14. 6.2015 22:12:56
  18. Wong, S.K.M.: On modelling information retrieval with probabilistic inference (1995) 0.01
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    Abstract
    Examines and extends the logical models of information retrieval in the context of probability theory and extends the applications of these fundamental ideas to term weighting and relevance. Develops a unified framework for modelling the retrieval process with probabilistic inference to provide a common conceptual and mathematical basis for many retrieval models, such as Boolean, fuzzy sets, vector space, and conventional probabilistic models. Employs this framework to identify the underlying assumptions by each model and analyzes the inherent relationships between them. Although the treatment is primarily theoretical, practical methods for rstimating the required probabilities are provided by simple examples
  19. Zhang, W.; Korf, R.E.: Performance of linear-space search algorithms (1995) 0.01
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    Date
    2. 8.1996 10:29:15
  20. Hüther, H.: Selix im DFG-Projekt Kascade (1998) 0.01
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    Date
    25. 8.2000 19:55:29

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