Search (14 results, page 1 of 1)

  • × author_ss:"Frieder, O."
  1. Grossman, D.A.; Holmes, D.O.; Frieder, O.; Nguyen, M.D.; Kingsbury, C.E.: Improving accuracy and run-time performance for TREC-4 (1996) 0.03
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    Pages
    S.433-441
    Source
    The Fourth Text Retrieval Conference (TREC-4). Ed.: K. Harman
  2. Lundquist, C.; Frieder, O.; Holmes, D.O.; Grossman, D.: ¬A parallel relational database management system approach to relevance feedback in information retrieval (1999) 0.03
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    Date
    17. 1.2000 12:22:18
    Source
    Journal of the American Society for Information Science. 50(1999) no.5, S.413-426
  3. Aqeel, S.U.; Beitzel, S.M.; Jensen, E.C.; Grossman, D.; Frieder, O.: On the development of name search techniques for Arabic (2006) 0.01
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    Date
    22. 7.2006 17:20:20
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.728-739
  4. Grossman, D.A.; Frieder, O.: Information retrieval : algorithms and heuristics (2004) 0.01
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    Classification
    BCA (FH K)
    GHBS
    BCA (FH K)
    Pages
    XX, 332 S
  5. Cathey, R.J.; Jensen, E.C.; Beitzel, S.M.; Frieder, O.; Grossman, D.: Exploiting parallelism to support scalable hierarchical clustering (2007) 0.01
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    Abstract
    A distributed memory parallel version of the group average hierarchical agglomerative clustering algorithm is proposed to enable scaling the document clustering problem to large collections. Using standard message passing operations reduces interprocess communication while maintaining efficient load balancing. In a series of experiments using a subset of a standard Text REtrieval Conference (TREC) test collection, our parallel hierarchical clustering algorithm is shown to be scalable in terms of processors efficiently used and the collection size. Results show that our algorithm performs close to the expected O(n**2/p) time on p processors rather than the worst-case O(n**3/p) time. Furthermore, the O(n**2/p) memory complexity per node allows larger collections to be clustered as the number of nodes increases. While partitioning algorithms such as k-means are trivially parallelizable, our results confirm those of other studies which showed that hierarchical algorithms produce significantly tighter clusters in the document clustering task. Finally, we show how our parallel hierarchical agglomerative clustering algorithm can be used as the clustering subroutine for a parallel version of the buckshot algorithm to cluster the complete TREC collection at near theoretical runtime expectations.
    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.8, S.1207-1221
  6. Grossman, D.A.; Frieder, O.: Information retrieval : algorithms and heuristics (1998) 0.00
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    Footnote
    Rez. in: JASIS 51(2000) no.11, S.1063-1064 (H.E. Williams)
    Pages
    254 S
  7. Lundquist, C.; Grossmann, D.A.; Reichart, J.; Holmes, D.O.; Chowdhury, A.; Frieder, O.: Using relevance feedback within the relational model for TREC-5 (1997) 0.00
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    Pages
    S.405-414
  8. Yee, W.G.; Nguyen, L.T; Frieder, O.: ¬A view of the data on P2P file-sharing systems (2009) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.2132-2141
  9. Soo, J.; Frieder, O.: On searching misspelled collections (2015) 0.00
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.6, S.1294-1298
  10. Ruocco, A.S.; Frieder, O.: Clustering and classification of large document bases in a parallel environment (1997) 0.00
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    Source
    Journal of the American Society for Information Science. 48(1997) no.10, S.932-943
  11. Fox, K.L.; Frieder, O.; Knepper, M.M.; Snowberg, E.J.: SENTINEL: a multiple engine information retrieval and visualization system (1999) 0.00
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    Source
    Journal of the American Society for Information Science. 50(1999) no.7, S.616-625
  12. Aljlayl, M.; Frieder, O.; Grossman, D.: On bidirectional English-Arabic search (2002) 0.00
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    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.13, S.1139-1151
  13. Beitzel, S.M.; Jensen, E.C.; Chowdhury, A.; Frieder, O.; Grossman, D.: Temporal analysis of a very large topically categorized Web query log (2007) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 58(2007) no.2, S.166-178
  14. Urbain, J.; Goharian, N.; Frieder, O.: Probabilistic passage models for semantic search of genomics literature (2008) 0.00
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    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.2008-2023