YoVDO

Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation - Session M3.5

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

Tags

Recommendation Systems Courses Machine Learning Courses E-commerce Courses Information Retrieval Courses User Behavior Analysis Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a critical analysis of next basket recommendation systems in this 16-minute conference talk from SIGIR 2024. Delve into the question of whether current approaches are truly achieving better beyond-accuracy performance. Join authors Ming Li, Yuanna Liu, Sami Jullien, Mozhdeh Ariannezhad, Andrew Yates, Mohammad Aliannejadi, and Maarten de Rijke as they examine the effectiveness of recommendation systems, focusing on metrics beyond traditional accuracy measures. Gain insights into the challenges and potential improvements in next basket recommendation algorithms, and understand the implications for real-world applications in e-commerce and personalized shopping experiences.

Syllabus

SIGIR 2024 M3.5 [fp] Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation


Taught by

Association for Computing Machinery (ACM)

Related Courses

Mining Massive Datasets
Stanford University via edX
Nearest Neighbor Collaborative Filtering
University of Minnesota via Coursera
Practical Deep Learning For Coders
fast.ai via Independent
Data Mining: Theories and Algorithms for Tackling Big Data | 数据挖掘:理论与算法
Tsinghua University via edX
ความรู้พื้นฐานเกี่ยวกับบิ๊กดาตา | Big Data Concept
Sukhothai Thammathirat Open University via ThaiMOOC