Search (58 results, page 1 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  1. Joss, M.W.; Wszola, S.: ¬The engines that can : text search and retrieval software, their strategies, and vendors (1996) 0.04 
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    Abstract
    Traces the development of text searching and retrieval software designed to cope with the increasing demands made by the storage and handling of large amounts of data, recorded on high data storage media, from CD-ROM to multi gigabyte storage media and online information services, with particular reference to the need to cope with graphics as well as conventional ASCII text. Includes details of: Boolean searching, fuzzy searching and matching; relevance ranking; proximity searching and improved strategies for dealing with text searching in very large databases. Concludes that the best searching tools for CD-ROM publishers are those optimized for searching and retrieval on CD-ROM. CD-ROM drives have relatively lower random seek times than hard discs and so the software most appropriate to the medium is that which can effectively arrange the indexes and text on the CD-ROM to avoid continuous random access searching. Lists and reviews a selection of software packages designed to achieve the sort of results required for rapid CD-ROM searching
    Date
    12. 9.1996 13:56:22
  2. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.04 
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    Date
    22. 3.2008 12:26:32
    RSWK
    Online-Recherche / Mathematische Methode
    Subject
    Online-Recherche / Mathematische Methode
  3. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.03 
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  4. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.03 
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    Abstract
    A relevancy-ranking algorithm for a natural language interface to Boolean online public access catalogs (OPACs) was formulated and compared with that currently used in a knowledge-based search interface called the E-Referencer, being developed by the authors. The algorithm makes use of seven weIl-known ranking criteria: breadth of match, section weighting, proximity of query words, variant word forms (stemming), document frequency, term frequency and document length. The algorithm converts a natural language query into a series of increasingly broader Boolean search statements. In a small experiment with ten subjects in which the algorithm was simulated by hand, the algorithm obtained good results with a mean overall precision of 0.42 and mean average precision of 0.62, representing a 27 percent improvement in precision and 41 percent improvement in average precision compared to the E-Referencer. The usefulness of each step in the algorithm was analyzed and suggestions are made for improving the algorithm.
    Content
    "Most Web search engines accept natural language queries, perform some kind of fuzzy matching and produce ranked output, displaying first the documents that are most likely to be relevant. On the other hand, most library online public access catalogs (OPACs) an the Web are still Boolean retrieval systems that perform exact matching, and require users to express their search requests precisely in a Boolean search language and to refine their search statements to improve the search results. It is well-documented that users have difficulty searching Boolean OPACs effectively (e.g. Borgman, 1996; Ensor, 1992; Wallace, 1993). One approach to making OPACs easier to use is to develop a natural language search interface that acts as a middleware between the user's Web browser and the OPAC system. The search interface can accept a natural language query from the user and reformulate it as a series of Boolean search statements that are then submitted to the OPAC. The records retrieved by the OPAC are ranked by the search interface before forwarding them to the user's Web browser. The user, then, does not need to interact directly with the Boolean OPAC but with the natural language search interface or search intermediary. The search interface interacts with the OPAC system an the user's behalf. The advantage of this approach is that no modification to the OPAC or library system is required. Furthermore, the search interface can access multiple OPACs, acting as a meta search engine, and integrate search results from various OPACs before sending them to the user. The search interface needs to incorporate a method for converting the user's natural language query into a series of Boolean search statements, and for ranking the OPAC records retrieved. The purpose of this study was to develop a relevancyranking algorithm for a search interface to Boolean OPAC systems. This is part of an on-going effort to develop a knowledge-based search interface to OPACs called the E-Referencer (Khoo et al., 1998, 1999; Poo et al., 2000). E-Referencer v. 2 that has been implemented applies a repertoire of initial search strategies and reformulation strategies to retrieve records from OPACs using the Z39.50 protocol, and also assists users in mapping query keywords to the Library of Congress subject headings."
    Source
    Electronic library. 22(2004) no.2, S.112-120
  5. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.02 
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    Date
    30. 3.2001 13:32:22
  6. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.02 
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    Date
    25. 8.2005 17:42:22
  7. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02 
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    Date
    14. 6.2015 22:12:44
  8. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.02 
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    Date
    14. 6.2015 22:12:56
  9. Notess, G.R.: Search engine relevance : the never-ending quest (2000) 0.02 
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    Source
    Online. 24(2000) no.3, S.35-40
  10. Jones, K.: Linguistic searching versus relevance ranking : DR-LINK and TARGET (1999) 0.02 
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    Source
    Online and CD-ROM review. 23(1999) no.2, S.67-80
  11. Feder, J.D.; Hobbs, E.T.: Speech recognition and full-text retrieval : interface and integration (1995) 0.02 
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    Source
    Proceedings of the 16th National Online Meeting 1995, New York, 2-4 May 1995. Ed.: M.E. Williams
  12. Jascó, P.: Mapping algorithms to translate natural language questions into search queries for Web databases (1997) 0.02 
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    Source
    Proceedings of the 18th National Online Meeting 1997, New York, 13.-15.5.1997. Ed.: M.E. Williams
  13. Tenopir, C.: Online databases : natural language searching with WIN (1993) 0.02 
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    Abstract
    WESTLAW is one of the first major commercial online systems to embrace both natural language input and partial match searching. Provides a backgroud to WESTLAW. Explains how the WESTLAW Is Natural (WIN) search engine works. Some searchers find that when searching with commands and Boolean logic, results differ drastically from those produces by searching with WIN. Discusses exact match Boolean logic search engines
  14. Ojala, M.: Decisions, decisions, RANK decisions (1994) 0.02 
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    Abstract
    Describes the RANK command which enables searchers of DIALOG databases do statistical analysis online. Describes the basic features of the ranking command. The fields to which this command can be applied run into the thousands. Shows how RANK can be used for content analysis. Details the limitations of the command and compares it with the SORT command. Offers advice on ranking results without using this command
    Source
    Online. 18(1994) no.2, S.74-77
  15. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.01 
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    Date
    20. 1.2007 18:30:22
  16. Faloutsos, C.: Signature files (1992) 0.01 
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    Date
    7. 5.1999 15:22:48
  17. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.01 
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    Date
    22. 3.2003 19:27:23
  18. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.01 
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    Date
    22. 8.2014 17:05:18
  19. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.01 
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    Date
    13. 9.2014 14:45:22
  20. Gauch, S.; Smith, J.B.: ¬An expert system for automatic query reformation (1993) 0.01 
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    Abstract
    Unfamiliarity with search tactics creates difficulties for many users of online retrieval systems. User observations indicate that even experienced searchers use vocabulary incorrectly and rarely reformulate their queries. To address these problems, an expert system for online search assistance was developed. This prototype automatically reformulates queries to improve the search results, and ranks the retrieved passages to speed the identification of relevant information. User's search performance using the expert system was compared with their search performance using an online thesaurus. The following conclusions were reached: (1) the expert system significantly reduced the number of queries necessary to find relevant passages compared with the user searching alone or with the thesaurus. (2) The expert system produced marginally significant improvements in precision compared with the user searching on their own. There was no significant difference in the recall achieved by the three system configurations. (3) Overall, the expert system ranked relevant passages above irrelevant passages

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