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06-APR-2017

Resolved dataset download problems Figured out a way to convert .h5 to csv ... Only 77% of the songs occur both in the features data and triplets data. So triplets data was pruned.

Can now work on all 3 methods using this.

  1. features.csv for Content-Based
  2. triplets.csv for Collaborative
  3. both for Deep

Work to be done:

  1. @Deepika: feature processing (normalization etc) and network architecture
  2. @Raghav: content based recommendation
  3. @Tejas: Collaborative Filtering

Tejas:

I am reading my NLP slides that talk about efficient similarity measurement.
We could potentially use that for our purposes.

19-APR-2017

Content-based recommendation code working. Results stored in ./results

Decided to use lyrics as inputs to the deep-network. Needs formatting and linking MSD Song-id to Musixmatch Track-id. Collaborative filtering in pipeline. top-n similar users using Pearson correlation found out. Working on Recommendations now.

Agenda for 20th:

  1. Complete Project Progress Report
  2. Formulate Deep Network Architecture

04-MAY-2017

  • Data extracted from Bag-of-Words and stored in csv file after many strenuous attempts of a rather boring task.
  • Data split as train-test-valid

08-MAY-2017 Three configurations:

  1. input = top-100 words
  2. input = all words
  3. input = embeddings obtained from Auto-encoder/ tSNE

We aim to compare the outputs of these three in the report.

To-do:

  1. Network architecture
  2. Recommendation system
  3. Comparisons of 3 approaches
  4. Specific examples to show the predictions
  5. Report
  6. Video