arrow_back Unsupervised Catalog Generation with Clustering, Reinforcement and More
Improving product discovery via Hierarchical Recommendations!
Submitted by Neha Kumari (@neha-kumari) on Friday, 5 April 2019
Session type: Lecture Session type: Full talk of 40 mins
A recommendation engine’s primary goal is to surface personalised & relevant content to the user, content which satisfies explicit intent as well as serendipitous content that would otherwise be invisible. E-commerce categories such as Lifestyle, have a lot of flux, the trends last for a short time window and have their demand distributed across an extensive selection. In such cases, recommending product collections can be a better idea instead of individual products.
In this talk I will be talking about the recommendation system at Flipkart, our journey towards recommending collection and how it improved the product discovery and helped in solving cold start problem. I will also cover the relevance algorithm used which is a hybrid of collaborative and content-based recommendation, and how this is achieved at scale, where we have catalogue consisting of ~400M products and this will be ever growing in this ecommerce world.
The Why ?
1. To solve cold start problem and to improve product discovery which aids to coverage
2. Increasing basket size and improving engagement post purchase
3. Cross category discovery and search result augmentation
- Introduction to recommendation system at Flipkart
- Problem in hand
- Our journey towards recommending collections
- How hierarchical product taxonomies can be leveraged to solve cold-start problem and improving product discovery
- Relevance algorithm@scale
- Captivating findings and results
Neha is a software developer with Recommendation team at Flipkart. She has worked on building scalable systems for product recommendations and personalisation. In the past she has also worked on Natural Language Processing. She is interested in building robust data processing pipelines at scale, and applying Machine Learning to solve challenging problems . She has graduated from IIT BHU. While not working on official projects, she involves herself in technical writing and blogging. She also contributes to the open source world by answering technical questions.