Search & Recommendations Architecture powering Sensy TV Remote app
How do you build a search and recommendations layer over a CRUD app? What are the challenges? How can python libraries and projects be leveraged to solve problems like auto-complete, full text search, “more like this” recommendations?
This talk will present a case study of search and recommendations systems architecture of Sensy TV Guide and Remote app. Topics will include
- Store data, serializing and delivering it to the app
- Built auto-complete suggestions with focus on low latencies
- Full text & Filtering on a dataset
- Creating an infinite content feed based on a users profile
Elvis D’Souza plays with TV, mobile & data at Sensy, a TV guide and remote startup.