NDLI: Privacy-preserving Hybrid Recommender System

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Content Provider	ACM Digital Library
Author	Tang, Qiang Wang, Husen
Abstract	Privacy issues in recommender systems have attracted the attention of researchers for many years. So far, a number of solutions have been proposed. Unfortunately, most of them are far from practical as they either downgrade the utility or are very inefficient. In this paper, we aim at a more practical solution, by proposing a privacy-preserving hybrid recommender system which consists of an incremental matrix factorization (IMF) component and a user-based collaborative filtering (UCF) component. The IMF component provides the fundamental utility while it allows the service provider to efficiently learn feature vectors in plaintext domain, and the UCF component improves the utility while allows users to carry out their computations in an offline manner. Leveraging somewhat homomorphic encryption (SWHE) schemes, we provide privacy-preserving candidate instantiations for both components. Our experiments demonstrate that the hybrid solution is much more efficient than existing solutions.
Starting Page	59
Ending Page	66
Page Count	8
File Format	PDF
ISBN	9781450349703
DOI	10.1145/3055259.3055268
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-04-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Privacy Recommender Homomorphic encryption
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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Privacy-preserving Hybrid Recommender System