Search (1 results, page 1 of 1)

  • × theme_ss:"Retrievalstudien"
  • × author_ss:"Chaudhry, A.S."
  1. Shafique, M.; Chaudhry, A.S.: Intelligent agent-based online information retrieval (1995) 0.02
    0.017623993 = product of:
      0.052871976 = sum of:
        0.052871976 = weight(_text_:based in 3851) [ClassicSimilarity], result of:
          0.052871976 = score(doc=3851,freq=6.0), product of:
            0.15283063 = queryWeight, product of:
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.050723847 = queryNorm
            0.34595144 = fieldWeight in 3851, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.0129938 = idf(docFreq=5906, maxDocs=44218)
              0.046875 = fieldNorm(doc=3851)
      0.33333334 = coord(1/3)
    
    Abstract
    Describes an intelligent agent based information retrieval model. The relevance matrix used by the intelligent agent consists of rows and columns; rows represent the documents and columns are used for keywords. Entries represent predetermined weights of keywords in documents. The search/query vector is constructed by the intelligent agent through explicit interaction with the user, using an interactive query refinement techniques. With manipulation of the relevance matrix against the search vector, the agent uses the manipulated information to filter the document representations and retrieve the most relevant documents, consequently improving the retrieval performance. Work is in progress on an experiment to compare the retrieval results from a conventional retrieval model and an intelligent agent based retrieval model. A test document collection on artificial intelligence has been selected as a sample. Retrieval tests are being carried out on a selected group of researchers using the 2 retrieval systems. Results will be compared to assess the retrieval performance using precision and recall matrices