Search (104 results, page 1 of 6)

  • × theme_ss:"Retrievalalgorithmen"
  1. Liddy, E.D.; Diamond, T.; McKenna, M.: DR-LINK in TIPSTER (2000) 0.01 
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    Date
    16. 8.2002 12:28:52
  2. Niemi, T.; Junkkari, M.; Järvelin, K.; Viita, S.: Advanced query language for manipulating complex entities (2004) 0.00 
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  3. Qi, Q.; Hessen, D.J.; Heijden, P.G.M. van der: Improving information retrieval through correspondenceanalysis instead of latent semantic analysis (2023) 0.00 
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    Date
    15. 9.2023 12:28:29
  4. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.00 
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    Date
    6. 1.1997 18:30:28
    11. 9.2004 17:32:22
  5. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.00 
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    Abstract
    The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
    Date
    16.11.2008 16:22:48
  6. Ruthven, I.; Lalmas, M.: Selective relevance feedback using term characteristics (1999) 0.00 
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    Source
    Vocabulary as a central concept in digital libraries: interdisciplinary concepts, challenges, and opportunities : proceedings of the Third International Conference an Conceptions of Library and Information Science (COLIS3), Dubrovnik, Croatia, 23-26 May 1999. Ed. by T. Arpanac et al
  7. Dang, E.K.F.; Luk, R.W.P.; Allan, J.; Ho, K.S.; Chung, K.F.L.; Lee, D.L.: ¬A new context-dependent term weight computed by boost and discount using relevance information (2010) 0.00 
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    Abstract
    We studied the effectiveness of a new class of context-dependent term weights for information retrieval. Unlike the traditional term frequency-inverse document frequency (TF-IDF), the new weighting of a term t in a document d depends not only on the occurrence statistics of t alone but also on the terms found within a text window (or "document-context") centered on t. We introduce a Boost and Discount (B&D) procedure which utilizes partial relevance information to compute the context-dependent term weights of query terms according to a logistic regression model. We investigate the effectiveness of the new term weights compared with the context-independent BM25 weights in the setting of relevance feedback. We performed experiments with title queries of the TREC-6, -7, -8, and 2005 collections, comparing the residual Mean Average Precision (MAP) measures obtained using B&D term weights and those obtained by a baseline using BM25 weights. Given either 10 or 20 relevance judgments of the top retrieved documents, using the new term weights yields improvement over the baseline for all collections tested. The MAP obtained with the new weights has relative improvement over the baseline by 3.3 to 15.2%, with statistical significance at the 95% confidence level across all four collections.
  8. Gonnet, G.H.; Snider, T.; Baeza-Yates, R.A.: New indices for text : PAT trees and PAT arrays (1992) 0.00 
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  9. Mandl, T.: Web- und Multimedia-Dokumente : Neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen (2003) 0.00 
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  10. Behnert, C.; Borst, T.: Neue Formen der Relevanz-Sortierung in bibliothekarischen Informationssystemen : das DFG-Projekt LibRank (2015) 0.00 
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  11. Sparck Jones, K.: ¬A statistical interpretation of term specifity and its application in retrieval (1972) 0.00 
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    Source
    Journal of documentation. 28(1972), S.11-21
  12. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.00 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  13. Ruthven, T.; Lalmas, M.; Rijsbergen, K.van: Incorporating user research behavior into relevance feedback (2003) 0.00 
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    Abstract
    Ruthven, Mounia, and van Rijsbergen rank and select terms for query expansion using information gathered on searcher evaluation behavior. Using the TREC Financial Times and Los Angeles Times collections and search topics from TREC-6 placed in simulated work situations, six student subjects each preformed three searches on an experimental system and three on a control system with instructions to search by natural language expression in any way they found comfortable. Searching was analyzed for behavior differences between experimental and control situations, and for effectiveness and perceptions. In three experiments paired t-tests were the analysis tool with controls being a no relevance feedback system, a standard ranking for automatic expansion system, and a standard ranking for interactive expansion while the experimental systems based ranking upon user information on temporal relevance and partial relevance. Two further experiments compare using user behavior (number assessed relevant and similarity of relevant documents) to choose a query expansion technique against a non-selective technique and finally the effect of providing the user with knowledge of the process. When partial relevance data and time of assessment data are incorporated in term ranking more relevant documents were recovered in fewer iterations, however retrieval effectiveness overall was not improved. The subjects, none-the-less, rated the suggested terms as more useful and used them more heavily. Explanations of what the feedback techniques were doing led to higher use of the techniques.
  14. Behnert, C.; Plassmeier, K.; Borst, T.; Lewandowski, D.: Evaluierung von Rankingverfahren für bibliothekarische Informationssysteme (2019) 0.00 
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  15. Iker, H.P.: Solution of Boolean equations through the use of term weights to the base two (1967) 0.00 
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    Date
    14. 5.1999 11:03:28
  16. Lee, J.H.: Combining the evidence of different relevance feedback methods for information retrieval (1998) 0.00 
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    Date
    11. 8.2001 17:28:42
  17. Archuby, C.G.: Interfaces se recuperacion para catalogos en linea con salidas ordenadas por probable relevancia (2000) 0.00 
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    Date
    29. 1.1996 18:23:13
    Source
    Ciencia da informacao. 29(2000) no.3, S.5-13
  18. Crestani, F.: Combination of similarity measures for effective spoken document retrieval (2003) 0.00 
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    Journal of information science. 29(2003) no.2, S.87-96
  19. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.00 
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    Date
    30. 3.2001 13:32:22
  20. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.00 
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    Date
    25. 8.2005 17:42:22

Authors

Years

Languages

  • e 85
  • d 17
  • m 1
  • pt 1
  • More… Less…

Types

  • a 99
  • m 3
  • el 1
  • r 1
  • s 1
  • x 1
  • More… Less…

Themes

Subjects

Classifications