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Found 6 papers, 0 papers with code
Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems
To improve representation in search results and recommendations, we introduce end-to-end diversification, ensuring that diverse content flows throughout the various stages of these systems, from retrieval to ranking.
Recommending Dream Jobs in a Biased Real World
Machine learning is at the heart of recommender systems.
A relevance-scalability-interpretability tradeoff with temporally evolving user personas
The current work characterizes the users of a VoD streaming space through user-personas based on a tenure timeline and temporal behavioral features in the absence of explicit user profiles.
Sequential Relevance Maximization with Binary Feedback
For every product category, each type has an associated relevance feedback that is assumed to be binary: the category is either relevant or irrelevant.
Guess Who Rated This Movie: Identifying Users Through Subspace Clustering
It is often the case that, within an online recommender system, multiple users share a common account.
Privacy Tradeoffs in Predictive Analytics
Recent research has demonstrated that several private user attributes (such as political affiliation, sexual orientation, and gender) can be inferred from such data.
