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  • × author_ss:"Frieder, O."
  • × year_i:[1990 TO 2000}
  1. Lundquist, C.; Frieder, O.; Holmes, D.O.; Grossman, D.: ¬A parallel relational database management system approach to relevance feedback in information retrieval (1999) 0.02 
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    Date
    17. 1.2000 12:22:18
  2. 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)
  3. Ruocco, A.S.; Frieder, O.: Clustering and classification of large document bases in a parallel environment (1997) 0.00 
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    Abstract
    Proposes the use of parallel computing systems to overcome the computationally intense clustering process. Examines 2 operations: clustering a document set and classifying the document set. Uses a subset of the TIPSTER corpus, specifically, articles from the Wall Street Journal. Document set classification was performed without the large storage requirements for ancillary data matrices. The time performance of the parallel systems was an improvement over sequential systems times, and produced the same clustering and classification scheme. Results show near linear speed up in higher threshold clustering applications
  4. 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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    Abstract
    We describe a prototype Information Retrieval system; SENTINEL, under development at Harris Corporation's Information Systems Division. SENTINEL is a fusion of multiple information retrieval technologies, integrating n-grams, a vector space model, and a neural network training rule. One of the primary advantages of SENTINEL is its 3-dimensional visualization capability that is based fully upon the mathematical representation of information with SENTINEL. The 3-dimensional visualization capability provides users with an intuitive understanding, with relevance/query refinement techniques athat can be better utilized, resulting in higher retrieval precision

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