In the Search & Recommendation group of Naver Labs, we are inventing the next generation of search and recommendation engines, which have to be multi-modal, multi-stakeholder, unbiased and transparent.
Diversity in Search and Recommendation results has long been recognized as a key factor for improving user satisfaction and long-term engagement, as well as a way to prevent filter bubbles and bias amplification. Traditional approaches enforce diversity by transforming relevance scores into marginalised utility scores capturing the “submodular” nature of the problem, often based on heuristics. More recent approaches aim at directly expressing the problem as a “learning-to-diversify” task, using a paradigm very similar to the supervised “Learning-to-Rank” one. As alternative ways, the problem can be expressed as a sequential decision making process, solved typically by reinforcement learning methods or, even more recently, as a transformer-based global multi-variate ranking task.
The goal of this internship is to compare these different approaches and to unify them into a single framework, where the diversification properties naturally emerge from the architecture of the models and from the loss function used for their training.
This internship will be supervised by Dr Jean-Michel Renders.
Diversity in Search & Recommendation, Reinforcement Learning, Sequential Decision Making, Set-wise/List-wise Learning-to-Rank, Self-Attention and Transformer-based models
NAVER LABS is a world class team of self-motivated and highly engaged researchers, engineers and interface designers collaborating together to create next generation ambient intelligence technology and services that are rich with the organic understanding they have of users, their contexts and situations.
Since 2013 LABS has led NAVER’s innovation in technology through products such as the AI-based translation app ‘Papago’, the omni-tasking web browser ‘Whale’, the virtual AI assistant ‘WAVE’, in-vehicle information entertainment system ‘AWAY’ and M1, the 3D indoor mapping robot.
The team in Europe is multidisciplinary and extremely multicultural specializing in artificial intelligence, machine learning, computer vision, natural language processing, UX and ethnography. We collaborate with many partners in the European scientific community on R&D projects.
NAVER LABS Europe is located in the south east of France in Grenoble. The notoriety of Grenoble comes from its exceptional natural environment and scientific ecosystem with 21,000 jobs in public and private research. It is home to 1 of the 4 French national institutes in AI called MIAI (Multidisciplinary Innovation in Ai) It has a large student community (over 62,000 students) and is a lively and cosmopolitan place, offering a host of leisure opportunities. Grenoble is close to both the Swiss and Italian borders and is the ideal place for skiing, hiking, climbing, hang gliding and all types of mountain sports.
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