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Implementation of Sequential Pattern mining using Time interval weights

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Tejas1908/Sequential-Pattern-mining-using-TiW

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Sequential-Pattern-mining-using-TiW

This repository contains an implementation of the paper "Mining weighted sequential patterns in a sequence database with a time-interval weight" by Joong Hyuk Chang, to fulfil the credit requirements for the course Data Warehousing and Data Mining.

The following is the folder structure of the repository:

  1. Code
    i.Implementation.ipynb : contains the main code of implementation
    ii. dataset_extraction.py : supporting and test file
    iii. test.ipynb : supporting and test file
    iv. plotting.py : supporting and test file
  2. Datasets : contain the various generated datasets for the data mining project
  3. Presentation.pdf : contains the slides used for project proposal and progress
  4. Report.pdf : contains a detailed report of the project including dataset details,algorithms used in implementation and our contributions.
  5. sample.pat : sample data files for reference
  6. sample.data : sample data files for reference

Dependencies
1.random
2.matplotlib

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