A heterogeneous graph-based recommendation simulator

Conference · Tue Jan 01 00:00:00 EST 2013

OSTI ID:1157174

Yeonchan, Ahn ^[1]; Sungchan, Park ^[1]; Lee, Matt Sangkeun ^[2]; Sang-goo, Lee ^[1]

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1. Seoul National University
2. ORNL

Heterogeneous graph-based recommendation frameworks have flexibility in that they can incorporate various recommendation algorithms and various kinds of information to produce better results. In this demonstration, we present a heterogeneous graph-based recommendation simulator which enables participants to experience the flexibility of a heterogeneous graph-based recommendation method. With our system, participants can simulate various recommendation semantics by expressing the semantics via meaningful paths like User Movie User Movie. The simulator then returns the recommendation results on the fly based on the user-customized semantics using a fast Monte Carlo algorithm.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Work for Others (WFO)
• DOE Contract Number: DE-AC05-00OR22725
• OSTI ID: 1157174
• Resource Relation: Conference: Proceedings of the 7th ACM conference on Recommender systems (RecSys 2013), Hongkong, China, 20131012, 20131016
• Country of Publication: United States
• Language: English