New York, NY, United States of America

Hugues Bouchard


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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3 patents (USPTO):Explore Patents

Title: Hugues Bouchard: Innovator in Personalizing Recommendations

Introduction

Hugues Bouchard is a notable inventor based in New York, NY (US). He has made significant contributions to the field of personalized recommendations, holding a total of 3 patents. His work focuses on enhancing user experience through innovative methods and systems.

Latest Patents

One of Hugues Bouchard's latest patents is titled "Personalizing explainable recommendations with bandits." This patent describes methods, systems, and computer program products that personalize recommendations of items with associated explanations. The embodiments utilize contextual bandits to create personalized explainable recommendations, referred to as 'recsplanations.' The system, known as "Bart," learns and predicts user satisfaction metrics such as click-through rates and consumption probabilities for various combinations of items, explanations, and contexts. Through logging and contextual bandit retraining, Bart can learn from its mistakes in an online setting, continuously improving the recommendation process.

Career Highlights

Hugues Bouchard is currently employed at Spotify AB, where he applies his expertise in developing innovative solutions for personalized user experiences. His work at Spotify has positioned him as a key player in the tech industry, particularly in the realm of recommendation systems.

Collaborations

Hugues collaborates with talented individuals such as James E McInerney and Benjamin Lacker. Their combined efforts contribute to the advancement of technology in personalized recommendations.

Conclusion

Hugues Bouchard's innovative work in personalizing recommendations showcases his commitment to enhancing user experiences through technology. His contributions are paving the way for more effective and engaging recommendation systems in the digital landscape.

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