Positive and Negative Critiquing for VAE-based Recommenders
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Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...
We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...
In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...
The ever-growing amount of online information calls for Personalization. Among the various personalization systems, recommenders have become increasingly popular in recent years. Recommenders typically use collaborative filtering to suggest the most releva ...
EPFL2018
User profiling is a useful primitive for constructing personalised services, such as content recommendation. In the present paper we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local informatio ...
2014
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This paper presents a novel application of sentiment analysis to recommender systems relying on explicit one-class user feedback (favorites or likes), namely joint models of unary feedback and sentiment of free-form user comments. This combination is achie ...
Elsevier2016
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Recent studies have shown that providing personalized explanations alongside recommendations increases trust and perceived quality. Furthermore, it gives users an opportunity to refine the recommendations by critiquing parts of the explanations. On one han ...
Modern technologies enable us to record sequences of online user activity at an unprecedented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating-prediction paradigm, ignoring temporal ...
Finding relevant content is one of the core activities of users interacting with a content repository, be it knowledge workers using an organizational knowledge management system at a workplace or self-regulated learners collaborating in a learning environ ...
2016
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Interest in developing user-centered sensing technologies for personalized behavior change has gained significant momentum. However, very little research work has been done to understand issues relative to user readiness and adoption of the sensing technol ...
