Samsung Electronics Co., Ltd.

Telefonaktiebolaget Lm Ericsson (Publ)

Tong Yu

Hongxia Jin

Yilin Shen

Julien Forgeat

Alvin Jude Hari Haran

Described is a system for providing improved exploration for an interactive recommendation system by leveraging intuitive user feedback. The recommendation system may provide images of recommend items and receive user feedback preferences in the form of a natural language expression. Traditional techniques for interactive recommendation systems typically rely on restricted forms of user feedback such as binary relevance responses, or feedback based on a fixed set of relative attributes. In contrast, the recommendation system described herein introduces a new approach to interactive image recommendation (or image search) that enables users to provide feedback via natural language, allowing for a more natural and effective interaction. The recommendation system may be based on formulating the task of natural-language-based interactive image recommendation as a reinforcement learning problem, and reward the recommendation system for improving the rank of the target image during each iterative interaction.

Exploration for interactive recommendation system, method, and computer program product

A system and method are described herein for improving content-based (CB) filtering to find other items similar to a particular item. For example, the system and method can operate to (1) collect ground truth from users, experts or non-experts for a subset of items in a library; (2) build similarity model(s) against the collected ground truth and evaluate this/these similarity model(s) for generalizability to all items in the library, and (3) build recommendations for users based on knowledge elicited from the users themselves, combined with the similarity scores in the built similarity model(s).

Growing community of inventors

Mountain View, CA, United States of America

Tong Yu