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  • × theme_ss:"Retrievalalgorithmen"
  1. Rada, R.; Barlow, J.; Potharst, J.; Zanstra, P.; Bijstra, D.: Document ranking using an enriched thesaurus (1991) 0.01 
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  2. Aigrain, P.; Longueville, V.: ¬A model for the evaluation of expansion techniques in information retrieval systems (1994) 0.01 
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  3. Mutschke, P.: Autorennetzwerke : Verfahren zur Netzwerkanalyse als Mehrwertdienste für Informationssysteme (2004) 0.01 
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  4. Mayr, P.: Bradfordizing als Re-Ranking-Ansatz in Literaturinformationssystemen (2011) 0.01 
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  5. Mayr, P.: Bradfordizing mit Katalogdaten : Alternative Sicht auf Suchergebnisse und Publikationsquellen durch Re-Ranking (2010) 0.01 
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  6. Van der Veer Martens, B.; Fleet, C. van: Opening the black box of "relevance work" : a domain analysis (2012) 0.01 
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    Abstract
    In response to Hjørland's recent call for a reconceptualization of the foundations of relevance, we suggest that the sociocognitive aspects of intermediation by information agencies, such as archives and libraries, are a necessary and unexplored part of the infrastructure of the subject knowledge domains central to his recommended "view of relevance informed by a social paradigm" (2010, p. 217). From a comparative analysis of documents from 39 graduate-level introductory courses in archives, reference, and strategic/competitive intelligence taught in 13 American Library Association-accredited library and information science (LIS) programs, we identify four defining sociocognitive dimensions of "relevance work" in information agencies within Hjørland's proposed framework for relevance: tasks, time, systems, and assessors. This study is intended to supply sociocognitive content from within the relevance work domain to support further domain analytic research, and to emphasize the importance of intermediary relevance work for all subject knowledge domains.
  7. Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996) 0.01 
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    Date
    12. 9.1996 13:56:22
  8. Kelledy, F.; Smeaton, A.F.: Signature files and beyond (1996) 0.01 
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  9. 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) 0.01 
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    Date
    22. 3.2003 19:27:36
  10. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.01 
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    Date
    11. 9.2004 17:32:22
  11. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01 
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    Date
    1. 8.2008 9:44:22
  12. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.01 
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    Date
    22. 3.2003 19:30:19
  13. Maron, M.E.; Kuhns, I.L.: On relevance, probabilistic indexing and information retrieval (1960) 0.01 
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    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.39-46.
  14. Information retrieval : data structures and algorithms (1992) 0.01 
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    Content
    An edited volume containing data structures and algorithms for information retrieval including a disk with examples written in C. for prgrammers and students interested in parsing text, automated indexing, its the first collection in book form of the basic data structures and algorithms that are critical to the storage and retrieval of documents. ------------------Enthält die Kapitel: FRAKES, W.B.: Introduction to information storage and retrieval systems; BAEZA-YATES, R.S.: Introduction to data structures and algorithms related to information retrieval; HARMAN, D. u.a.: Inverted files; FALOUTSOS, C.: Signature files; GONNET, G.H. u.a.: New indices for text: PAT trees and PAT arrays; FORD, D.A. u. S. CHRISTODOULAKIS: File organizations for optical disks; FOX, C.: Lexical analysis and stoplists; FRAKES, W.B.: Stemming algorithms; SRINIVASAN, P.: Thesaurus construction; BAEZA-YATES, R.A.: String searching algorithms; HARMAN, D.: Relevance feedback and other query modification techniques; WARTIK, S.: Boolean operators; WARTIK, S. u.a.: Hashing algorithms; HARMAN, D.: Ranking algorithms; FOX, E.: u.a.: Extended Boolean models; RASMUSSEN, E.: Clustering algorithms; HOLLAAR, L.: Special-purpose hardware for information retrieval; STANFILL, C.: Parallel information retrieval algorithms
  15. Kantor, P.; Kim, M.H.; Ibraev, U.; Atasoy, K.: Estimating the number of relevant documents in enormous collections (1999) 0.01 
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  16. Crouch, C.J.; Crouch, D.B.; Chen, Q.; Holtz, S.J.: Improving the retrieval effectiveness of very short queries (2002) 0.01 
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    Abstract
    This paper describes an automatic approach designed to improve the retrieval effectiveness of very short queries such as those used in web searching. The method is based on the observation that stemming, which is designed to maximize recall, often results in depressed precision. Our approach is based on pseudo-feedback and attempts to increase the number of relevant documents in the pseudo-relevant set by reranking those documents based on the presence of unstemmed query terms in the document text. The original experiments underlying this work were carried out using Smart 11.0 and the lnc.ltc weighting scheme on three sets of documents from the TREC collection with corresponding TREC (title only) topics as queries. (The average length of these queries after stoplisting ranges from 2.4 to 4.5 terms.) Results, evaluated in terms of P@20 and non-interpolated average precision, showed clearly that pseudo-feedback (PF) based on this approach was effective in increasing the number of relevant documents in the top ranks. Subsequent experiments, performed on the same data sets using Smart 13.0 and the improved Lnu.ltu weighting scheme, indicate that these results hold up even over the much higher baseline provided by the new weights. Query drift analysis presents a more detailed picture of the improvements produced by this process.
  17. Quiroga, L.M.; Mostafa, J.: ¬An experiment in building profiles in information filtering : the role of context of user relevance feedback (2002) 0.01 
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    Abstract
    An experiment was conducted to see how relevance feedback could be used to build and adjust profiles to improve the performance of filtering systems. Data was collected during the system interaction of 18 graduate students with SIFTER (Smart Information Filtering Technology for Electronic Resources), a filtering system that ranks incoming information based on users' profiles. The data set came from a collection of 6000 records concerning consumer health. In the first phase of the study, three different modes of profile acquisition were compared. The explicit mode allowed users to directly specify the profile; the implicit mode utilized relevance feedback to create and refine the profile; and the combined mode allowed users to initialize the profile and to continuously refine it using relevance feedback. Filtering performance, measured in terms of Normalized Precision, showed that the three approaches were significantly different ( [small alpha, Greek] =0.05 and p =0.012). The explicit mode of profile acquisition consistently produced superior results. Exclusive reliance on relevance feedback in the implicit mode resulted in inferior performance. The low performance obtained by the implicit acquisition mode motivated the second phase of the study, which aimed to clarify the role of context in relevance feedback judgments. An inductive content analysis of thinking aloud protocols showed dimensions that were highly situational, establishing the importance context plays in feedback relevance assessments. Results suggest the need for better representation of documents, profiles, and relevance feedback mechanisms that incorporate dimensions identified in this research.
  18. Shah, B.; Raghavan, V.; Dhatric, P.; Zhao, X.: ¬A cluster-based approach for efficient content-based image retrieval using a similarity-preserving space transformation method (2006) 0.01 
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  19. Li, J.; Willett, P.: ArticleRank : a PageRank-based alternative to numbers of citations for analysing citation networks (2009) 0.01 
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  20. Cheng, C.-S.; Chung, C.-P.; Shann, J.J.-J.: Fast query evaluation through document identifier assignment for inverted file-based information retrieval systems (2006) 0.01 
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