Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems

DOI10.1287/mnsc.1060.0619zbMath1232.91426OpenAlexW3125836118MaRDI QIDQ3116128

Hsinchun Chen, Zan Huang, Daniel D. Zeng

Publication date: 21 February 2012

Published in: Management Science (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/8b20c7cc845ec5cf1a75f1b1b49d2921b62c3ff0

zbMATH Keywords

collaborative filteringrecommender systemstopological featuresrandom graph theoryconsumer-purchase behavior

Mathematics Subject Classification ID

Social networks; opinion dynamics (91D30) Random graphs (graph-theoretic aspects) (05C80) Consumer behavior, demand theory (91B42)

Related Items (8)

Long-term effects of user preference-oriented recommendation method on the evolution of online system ⋮ Location-Aware Real-Time Recommender Systems for Brick-and-Mortar Retailers ⋮ Bipartite network influence analysis of a two-mode network ⋮ Optimization-Based Approaches for Maximizing Aggregate Recommendation Diversity ⋮ Tensorial graph learning for link prediction in generalized heterogeneous networks ⋮ Shilling Attack Detection—A New Approach for a Trustworthy Recommender System ⋮ EFFECTS OF THE HIGH-ORDER CORRELATION ON INFORMATION FILTERING ⋮ The recommender system for virtual items in MMORPGs based on a novel collaborative filtering approach

Uses Software

• Eigentaste

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