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A movie recommender system based on Information Retrieval and Data Integration Theory.

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MovieRecommend

Project Paper: https://www.overleaf.com/read/hbzdkxfpjhkx

A movie recommender system based on Information Retrieval and Data Integration Theory. Uses content-based matching to link a user's Twitter profile contents to movie information stored in a local MongoDB instance. These results are scored using a TF-IDF style weighting system, and displayed within a GUI designed using Python's tkinter library.

Three modes of recommendation:

  • Twitter: Recommendations based on a user's Twitter profile contents.
  • History: Recommendations based on a list of movies specified by the user (such as a watch history)
  • Tags: Recommendations based on a list of tags specified by the user (genres, topics, etc)

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