NDLI: Weighted Random Walk Sampling for Multi-Relational Recommendation

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Weighted Random Walk Sampling for Multi-Relational Recommendation

Content Provider	ACM Digital Library
Author	Vahedian, Fatemeh Burke, Robin Mobasher, Bamshad
Abstract	In the information overloaded web, personalized recommender systems are essential tools to help users find most relevant information. The most heavily-used recommendation frameworks assume user interactions that are characterized by a single relation. However, for many tasks, such as recommendation in social networks, user-item interactions must be modeled as a complex network of multiple relations, not only a single relation. Recently research on multi-relational factorization and hybrid recommender models has shown that using extended meta-paths to capture additional information about both users and items in the network can enhance the accuracy of recommendations in such networks. Most of this work is focused on unweighted heterogeneous networks, and to apply these techniques, weighted relations must be simplified into binary ones. However, information associated with weighted edges, such as user ratings, which may be crucial for recommendation, are lost in such binarization. In this paper, we explore a random walk sampling method in which the frequency of edge sampling is a function of edge weight, and apply this generate extended meta-paths in weighted heterogeneous networks. With this sampling technique, we demonstrate improved performance on multiple data sets both in terms of recommendation accuracy and model generation efficiency.
Starting Page	230
Ending Page	237
Page Count	8
File Format	PDF
ISBN	9781450346351
DOI	10.1145/3079628.3079685
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-07-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Multi-relational recommender system Weighted meta-path generation Weighted random walk sampling Heterogeneous information network Multi-relational matrix factorization
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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