Search (38 results, page 2 of 2)

  • × language_ss:"e"
  • × theme_ss:"Retrievalalgorithmen"
  • × type_ss:"a"
  1. 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
  2. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.01
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    Date
    31. 5.2004 19:22:06
  3. 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
  4. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01
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    Date
    1. 8.2008 9:44:22
  5. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.01
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    Date
    16.11.2008 16:22:48
  6. 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
  7. Kang, I.-H.; Kim, G.C.: Integration of multiple evidences based on a query type for web search (2004) 0.01
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  8. White, R.W.; Jose, J.M.; Ruthven, I.: Using top-ranking sentences to facilitate effective information access (2005) 0.01
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  9. 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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    Abstract
    Compressing an inverted file can greatly improve query performance of an information retrieval system (IRS) by reducing disk I/Os. We observe that a good document identifier assignment (DIA) can make the document identifiers in the posting lists more clustered, and result in better compression as well as shorter query processing time. In this paper, we tackle the NP-complete problem of finding an optimal DIA to minimize the average query processing time in an IRS when the probability distribution of query terms is given. We indicate that the greedy nearest neighbor (Greedy-NN) algorithm can provide excellent performance for this problem. However, the Greedy-NN algorithm is inappropriate if used in large-scale IRSs, due to its high complexity O(N2 × n), where N denotes the number of documents and n denotes the number of distinct terms. In real-world IRSs, the distribution of query terms is skewed. Based on this fact, we propose a fast O(N × n) heuristic, called partition-based document identifier assignment (PBDIA) algorithm, which can efficiently assign consecutive document identifiers to those documents containing frequently used query terms, and improve compression efficiency of the posting lists for those terms. This can result in reduced query processing time. The experimental results show that the PBDIA algorithm can yield a competitive performance versus the Greedy-NN for the DIA problem, and that this optimization problem has significant advantages for both long queries and parallel information retrieval (IR).
  10. Symonds, M.; Bruza, P.; Zuccon, G.; Koopman, B.; Sitbon, L.; Turner, I.: Automatic query expansion : a structural linguistic perspective (2014) 0.01
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  11. Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995) 0.01
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    Date
    22. 2.1996 11:20:06
  12. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01
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    Date
    22. 2.1996 13:14:10
  13. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01
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    Date
    22. 3.2003 19:35:46
  14. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.01
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    Date
    22. 7.2006 16:32:43
  15. Baloh, P.; Desouza, K.C.; Hackney, R.: Contextualizing organizational interventions of knowledge management systems : a design science perspectiveA domain analysis (2012) 0.01
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    Date
    11. 6.2012 14:22:34
  16. Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013) 0.01
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    Date
    22. 3.2013 19:34:49
  17. Henzinger, M.R.: Hyperlink analysis for the Web (2001) 0.01
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    Content
    Information retrieval is a computer science subfield whose goal is to find all documents relevant to a user query in a given collection of documents. As such, information retrieval should really be called document retrieval. Before the advent of the Web, IR systems were typically installed in libraries for use mostly by reference librarians. The retrieval algorithm for these systems was usually based exclusively on analysis of the words in the document. The Web changed all this. Now each Web user has access to various search engines whose retrieval algorithms often use not only the words in the documents but also information like the hyperlink structure of the Web or markup language tags. How are hyperlinks useful? The hyperlink functionality alone-that is, the hyperlink to Web page B that is contained in Web page A-is not directly useful in information retrieval. However, the way Web page authors use hyperlinks can give them valuable information content. Authors usually create hyperlinks they think will be useful to readers. Some may be navigational aids that, for example, take the reader back to the site's home page; others provide access to documents that augment the content of the current page. The latter tend to point to highquality pages that might be on the same topic as the page containing the hyperlink. Web information retrieval systems can exploit this information to refine searches for relevant documents. Hyperlink analysis significantly improves the relevance of the search results, so much so that all major Web search engines claim to use some type of hyperlink analysis. However, the search engines do not disclose details about the type of hyperlink analysis they perform- mostly to avoid manipulation of search results by Web-positioning companies. In this article, I discuss how hyperlink analysis can be applied to ranking algorithms, and survey other ways Web search engines can use this analysis.
  18. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.01
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    Source
    Electronic library. 22(2004) no.2, S.112-120

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