Talk Submission at Pycon India 2016
- What it is ??
- How it is done?
- Technologies used
- Data and Models
- Installation
- What is there inside the box 📦 ?
- Contributors
- Issues 🐛
How can we create a recommendation engine that is based both on user browsing history and product reviews? Can I create recommendations purely based on the 'intent' and 'context' of the search?
This talk will showcase how a recommendation engine can be built with user browser history and user-generated reviews using a state of the art technique - word2vec. We will create something that not only matches the existing recommender systems deployed by websites, but goes one step ahead - incorporating context to generate valid and innovative recommendations. The beauty of such a framework is that not only does it support online learning, but is also sensitive to minor changes in user tone and behavior.
The trick/secret sauce is - How do we account for the 'context' and build it in our systems? The talk will answer these questions and showcase effectiveness of such a recommender system.
- Subset of the engine's functionality was completed during a project undertaken at IASNLP 2016 held by Language Technology Research Center (LTRC), IIIT Hyderabad
- Google's Word2vec
- Gensim
- Numpy
- Flask, Redis.
- Rest of the models (User & Metadata) can be downloaded from https://s3.amazonaws.com/iasnlp-models/output_models.tar
- Amazon review data will be made available (for research purposes) on request. Please contact Julian McAuley (julian.mcauley@gmail.com) to obtain a link. Sample data files available at: http://jmcauley.ucsd.edu/data/amazon/
| File | Function |
|---|---|
| semsim_train.py | Main file to train models |
| preProcessing.py | Methods to preprocess and clean data before feeding for training |
| loadReviewModel.py | For loading review model |
| loadRedis.py | For loading redis model |
| loadMetaModel.py | For loading meta model |
| Author | Working As | contact @ |
|---|---|---|
| Manas Ranjan kar | Practice Lead @ Juxt Smart Mandate | @github |
| Akhil Gupta | Intern @ Amazon | @github |
| Vinay Kumar | MS @ IIT-KGP | @github |
You can tweet to Manas Ranjan Kar or Akhil Gupta if you can't get it to work. In fact, you should tweet us anyway.