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Pratima Gautam

  1. A Novel Approach For Discovery Multi Level Fuzzy Association Rule Mining.

    Втр, 03/23/2010 - 16:02 — SomNambul
    Authors: K. R. Pardasani, Pratima Gautam
    Subjects: Databases
    Abstract

    Finding multilevel association rules in transaction databases is most
    commonly seen in is widely used in data mining. In this paper, we present a
    model of mining multilevel association rules which satisfies the different
    minimum support at each level, we have employed fuzzy set concepts, multi-level
    taxonomy and different minimum supports to find fuzzy multilevel association
    rules in a given transaction data set. Apriori property is used in model to
    prune the item sets. The proposed model adopts a topdown progressively
    deepening approach to derive large itemsets.

  2. A Model for Mining Multilevel Fuzzy Association Rule in Database.

    Чт, 01/21/2010 - 16:01 — SomNambul
    Authors: Neelu Khare, K. R. Pardasani, Pratima Gautam
    Subjects: Databases
    Abstract

    The problem of developing models and algorithms for multilevel association
    mining pose for new challenges for mathematics and computer science. These
    problems become more challenging, when some form of uncertainty like fuzziness
    is present in data or relationships in data. This paper proposes a multilevel
    fuzzy association rule mining models for extracting knowledge implicit in
    transactions database with different support at each level. The proposed
    algorithm adopts a top-down progressively deepening approach to derive large
    itemsets.

Math-arch

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