NDLI: Non-user Generated Annotation on User Shared Images for Connection Discovery

Content Provider	IEEE Xplore Digital Library
Author	Ming Cheung She, J. Xiaopeng Li
Copyright Year	2015
Description	Author affiliation: HKUST-NIE Social Media Lab., Hong Kong Univ. of Sci. & Technol., Hong Kong, China (Ming Cheung; She, J.; Xiaopeng Li)
Abstract	Social graphs, representing the online friendships among users, are one of the most fundamental types of data for many social media applications, such as recommendation, virality prediction and marketing. However, this data may be unavailable due to the privacy concerns of users, or kept privately by social network operators, which makes such applications difficult. One of the possible solutions to discover user connections is to use shared content, especially images on online social networks, such as Flickr and Instagram. This paper investigates how non-user generated labels annotated on shared images can be used for connection discovery with different color-based and feature-based methods. The label distribution is computed to represent users, and followee/follower relationships are recommended based on the distribution similarity. These methods are evaluated with over 200k images from Flickr and it is proven that with non-user generated labels, user connections can be discovered, regardless of the method used. Feature-based methods are also proven to be 95% better than color-based methods, and 65% better than tag-based methods.
Starting Page	204
Ending Page	209
File Size	819032
Page Count	6
File Format	PDF
ISBN	9781509002146
DOI	10.1109/DSDIS.2015.113
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-11
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Visualization Image color analysis Connection discovery Media Tagging Big data Recommendation Annotation Online social network
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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