Main Reference PaperReducing the Search Space for Big Data Mining for Interesting Patterns from Uncertain Data, IEEE International Congress on Big Data, 2014.
  • The data is searched from huge amount of uncertain data like finding users interesting patterns from big data where data are in thousands of terabytes. For avoid wasting a lot of time and space in search the frequent patterns from uncertain Big data, this paper allows that users to express their interest in terms of succinct anti-monotone (SAM) constraints and uses MapReduce to mine uncertain Big data for frequent patterns that satisfy the user-specified constraints.

+ Description
  • The data is searched from huge amount of uncertain data like finding users interesting patterns from big data where data are in thousands of terabytes. For avoid wasting a lot of time and space in search the frequent patterns from uncertain Big data, this paper allows that users to express their interest in terms of succinct anti-monotone (SAM) constraints and uses MapReduce to mine uncertain Big data for frequent patterns that satisfy the user-specified constraints.

  • To achieve the space-efficient and time efficient in search the interesting pattern from uncertain data.

  • To reduce the computation by apply the constraints on map function.

+ Aim & Objectives
  • To achieve the space-efficient and time efficient in search the interesting pattern from uncertain data.

  • To reduce the computation by apply the constraints on map function.

  • To further reduce the search space and execution time in uncertain Big data, this work provides importance to frequency of items using weighting factors. It can reduce the nodes in the first level of tree, which leads to reduction in the size of the tree and execution time.

+ Contribution
  • To further reduce the search space and execution time in uncertain Big data, this work provides importance to frequency of items using weighting factors. It can reduce the nodes in the first level of tree, which leads to reduction in the size of the tree and execution time.

  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, Hadoop

+ Software Tools & Technologies
  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, Hadoop

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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