RecSysFR #9, September 27th 2018

Thanks to Fifty-Five for hosting this meetup! Only two talks for this edition.

Romain WARLOP — Fifty Five
Multi Task DPP for Basket Completion
Determinantal point processes (DPPs) have received significant attention in the recent years as an elegant model for a variety of machine learning tasks, due to their ability to elegantly model set diversity and item quality or popularity. Recent work has shown that DPPs can be effective models for product recommendation and basket completion tasks. We present an enhanced DPP model that is specialized for the task of basket completion, the multi-task DPP. We view the basket completion problem as a multi-class classification problem, and leverage ideas from tensor factorization and multi-class classification to design the multi-task DPP model. We evaluate our model on several real-world datasets, and find that the multi-task DPP provides significantly better predictive quality than a number of state-of-the-art models.
Cristian PEREZ, Stanislas MORBIEU — Kernix
Building a recommender system with Annoy and Word2Vec
The Kernix Lab will talk about the development of a recommender engine at the RecSys MeetUp. We will discuss both strategic and technical considerations for a production ready system. Technically, how we handle cold start, misspelled words and content high renewal rates will be shared.