NDLI: Pairwise learning to recommend with both users’ and items’ contextual information

Content Provider	IET Digital Library
Author	Huang, Zhenhua E, Shijia Zhang, Jiawen Zhang, Bo Ji, Zilian
Abstract	Exponential growth of information generated by social networks requires efficient and scalable recommendation techniques to produce useful results. Traditional methods have become unqualified because they consider only ratings instead of rankings in an item list, and they ignore social contextual information, which is valuable for predicting users’ preference. It is significant and challenging to fuse social contextual information into learning to recommendation methods. In this study, the authors first extend user latent features by exploiting users’ social relationship such as friendship or trust relations, and extend item latent features with concurrent items. Then they integrate both users’ and items’ social contextual information into a pairwise learning to recommendation model (named as UIContextRank) to enhance ranking accuracy and recommendation quality. Furthermore, they extend UIContextRank in a distributed environment to improve efficiency and scalability. The authors conduct experiments on both bidirectional and unidirectional social network datasets. The results show that their method significantly outperforms other approaches.
Starting Page	2084
Ending Page	2090
Page Count	7
ISSN	17518628
Volume Number	10
e-ISSN	17518636
Issue Number	Issue 16, Nov (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/10/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2016.0112
Journal	IET Communications
Publisher Date	2016-11-03
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Distributed Environment Information Network Items Contextual Information Knowledge Engineering Technique Learning in AI Pairwise Learning Social Contextual Information Social Network Social Networking (online) Social Relationship UIContextRank Unidirectional Social Network User Contextual Information
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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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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