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Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative Filtering

Offered By: Association for Computing Machinery (ACM) via YouTube

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Recommender Systems Courses Data Mining Courses Machine Learning Courses Neural Networks Courses Information Retrieval Courses

Course Description

Overview

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Explore the individuality and collectivity of intents behind interactions for graph collaborative filtering in this 15-minute conference talk presented at SIGIR 2024. Delve into the research conducted by Yi Zhang, Lei Sang, and Yiwen Zhang as they discuss their findings on improving graph-based recommendation systems. Gain insights into how understanding user intents, both individually and collectively, can enhance the performance of collaborative filtering algorithms in graph structures. Learn about the latest advancements in this field and their potential applications in various recommendation scenarios.

Syllabus

SIGIR 2024 T1.4 [fp] Exploring the Individuality and Collectivity of Intents behind Interactions


Taught by

Association for Computing Machinery (ACM)

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