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  • × author_ss:"Raghavan, V.V."
  • × year_i:[1990 TO 2000}
  1. Bollmann-Sdorra, P.; Raghavan, V.V.: On the delusiveness of adopting a common space for modelling IR objects : are queries documents? (1993) 0.01 
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    Abstract
    Many authors, who adopt the vector space model, take the view that documents, terms, queries, etc., are all elements within the same (conceptual) space. This view seems to be a natural one, given that documents and queries have the same vector notation. We show, however, that the structure of the query space can be very different from that of the document space. To this end, concepts like preference, similarity, term independence, and linearity, both in the document space and in the query space, are discussed. Our conclusion is that a more realistic and complete view of IR is obtained if we do not consider documents and queries to be elements of the same space. This conclusion implies that certain restrictions usually applied in the design of an IR system are obviated. For example, the retrieval function need not be interpreted as a similarity measure
  2. Bollmann-Sdorra, P.; Raghavan, V.V.: On the necessity of term dependence in a query space for weighted retrieval (1998) 0.01 
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    Abstract
    In recent years, in the context of the vector space model, the view, held by many researchers, that documents, queries, terms, etc., are all elements of a common space has been challenged (Bollmann-Sdorra & Raghavan, 1993). In particular, it was noted that term independence has to be investigated in the context of user preferences and it was shown, through counterexamples, that term independence can hold in the document space, but not in the query space and vice versa. In this article, we continue the investigation of query and document spaces with respect to the property of term independence. We prove, under realistic assumptions, that requiring term independence to hold in the query space is inconsistent with the goal of achieving better performance by means of weighted retrieval. The result that term independence in the query space is undesirable is obtained without making any assumption about wjether or not the property of term independence holds in the document space. The results of this article reinforce our position that the properties of document and query spaces must be investigated separately, since the document and query spaces do not necessarily have the same properties
  3. Raghavan, V.V.; Deogun, J.S.; Sever, H.: Knowledge discovery and data mining : introduction (1998) 0.00 
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    Abstract
    Defines knowledge discovery and database mining. The challenge for knowledge discovery in databases (KDD) is to automatically process large quantities of raw data, identifying the most significant and meaningful patterns, and present these as as knowledge appropriate for achieving a user's goals. Data mining is the process of deriving useful knowledge from real world databases through the application of pattern extraction techniques. Explains the goals of, and motivation for, research work on data mining. Discusses the nature of database contents, along with problems within the field of data mining

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