NDLI: Using user similarity to infer trust values in social networks regardless of direct ratings

Content Provider	IEEE Xplore Digital Library
Author	Mohammadhassanzadeh, H. Shahriari, H.R.
Copyright Year	2012
Description	Author affiliation: Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran (Mohammadhassanzadeh, H.; Shahriari, H.R.)
Abstract	Social networks recently get more attention on the Internet. Although they were introduced to facilitate relationships, now users may utilize them to get services such as experts' consultancy and marketing. Anyhow, users need a somehow proper estimation of trust in other users to make better decisions. Some trust evaluation mechanisms, which use direct ratings to calculate or propagate trust values, have been offered. However in social networks in which users only have binary relationship with each other, there is no direct rating value. Therefore a method is required to infer the values of trust and user reputation in social networks. In this paper, we propose a new method that employs user similarities to extract trust values without any need of direct rating. In our approach, user similarity is calculated from profile information and shared text via text-mining techniques. To show the effectiveness of our approach, it has been evaluated through rates gathered directly from the users. Comparing these rates with experimental results shows that the estimated trust values, obtained by this approach, are sufficiently acceptable. Besides the application of this approach in social networks, the proposed technique also can be used in direct rating mechanisms to evaluate correctness of trust values assigned by users, and consequently increase reliability of trust and reputation mechanisms against possible security threats.
Starting Page	66
Ending Page	72
File Size	697059
Page Count	7
File Format	PDF
ISBN	9781467323871
e-ISBN	9781467323864
DOI	10.1109/ISCISC.2012.6408193
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-13
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Text mining Correlation Social Networks Social network services Educational institutions Motion pictures Vectors Text Mining Reputation Reliability Trust User Similarity
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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