Main Reference PaperMining Temporal Patterns in Time Interval-based Data, IEEE Transactions on Knowledge and Data Engineering, July 2015.
  • In Sequential pattern mining, the pattern is discovered from the sequential events, since the relationship between two intervals is intrinsically complex. To simplify the processing of complex relationships among event intervals using endpoint representation and endtime representation. Proposed work also use the two novel algorithms ( TPMiner, Probabilistic Temporal Pattern), to discover three types of interval-based sequential patterns.

+ Description
  • In Sequential pattern mining, the pattern is discovered from the sequential events, since the relationship between two intervals is intrinsically complex. To simplify the processing of complex relationships among event intervals using endpoint representation and endtime representation. Proposed work also use the two novel algorithms ( TPMiner, Probabilistic Temporal Pattern), to discover three types of interval-based sequential patterns.

  • To reduce the search space of the mining process.

  • To evaluate the interval based pattern in endpoint and endtime representation.

+ Aim & Objectives
  • To reduce the search space of the mining process.

  • To evaluate the interval based pattern in endpoint and endtime representation.

  • A point based events also included in proposed algorithm, this makes an efficient way of mining the exact data from the database.

+ Contribution
  • A point based events also included in proposed algorithm, this makes an efficient way of mining the exact data from the database.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1 & J2SE

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1 & J2SE

  • B.E / B.Tech / M.E / M.Tech

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

  • 10 – 15 Days

+ Order To Delivery
  • 10 – 15 Days

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