Personalization in Practice
Methods and Applications — a WSDM ’21 Tutorial
By Dima Goldenberg, Kostia Kofman, Javier Albert, Sarai Mizrachi, Adam Horowitz and Irene Teinemaa
Personalization is one of the key applications in machine learning with widespread usage across e-commerce, entertainment, production, healthcare and many other industries. While various machine learning techniques present novel state-of-the-art advances and super-human performance year-over-year, personalization and recommender systems applications are often late-adopters of novel solutions due to problem hardness and implementation complexity.
This tutorial presents recent advances across the personalization industry and demonstrates their practical applications in real case-studies of world-leading online platforms. Key trends such as deep learning, causality and active exploration with bandits are depicted with real examples and demonstrated alongside their business considerations and implementation challenges.
Rising topics like explainability, fairness, natural interfaces and content generation are covered, touching on aspects of both technology and user experience. Our tutorial relies on recent advances in the field and on work conducted at Booking.com, where we implement personalization models on one of the world’s leading online travel platform.
Tutorial Outline
The outline of the tutorial is as follows. We begin by introducing the traditional personalization landscape and recommendation systems, along with their unique challenges in implementations, and then cover key recent trends. We continue with a deep dive into three state-of-the-art personalization solutions, covering theory and practical implementations in the field. Lastly, we overview the topic from the user perspective, covering the relevance of target users’ perceptions of personalization. The total duration of the tutorial is four and a half hours. The detailed format and schedule are as follows:
Detailed Schedule
Monday, March 8th 2021
- 14:00 — Trends in Personalization (50 mins) Dima Goldenberg
- 15:00 — Sequence Modeling (30 mins) Sarai Mizrachi
- 15:40 — Uplift Modeling (80 mins) Irene Teinemaa & Javier Albert
- 17:10 — Contextual Bandits (35 mins) Kostia Kofman
- 17:50 — User Perception (35 min) Adam Horowitz
Relevance to the community
Personalization is a key application of the web-search and data mining fields. As such, it has topical importance for both research and practical implementation. Our aim is to briefly cover the topic of personalization by introducing recent, nontrivial trends in the field and by demonstrating possible applications.
The main focuses of the tutorial are:
(i) to survey key trends in personalization;
(ii) to introduce a selection of advanced techniques;
(iii) to demonstrate practical personalization implementations.
This tutorial is suitable both as an introduction for new practitioners in the field and to bring experts up to date with recent research and walk-throughs of novel applications.
Tutorial Materials
Detailed agenda and references can be found on ACM digital library (pdf).
For citations, please refer to:
Goldenberg, D., Kofman, K., Albert, J., Mizrachi, S., Horowitz, A., & Teinemaa, I. (2021, March). Personalization in practice: Methods and applications. In Proceedings of the 14th ACM international conference on web search and data mining (pp. 1123–1126).
Full tutorial slides and materials are available here.
