Photo identity tag suggestion using only social network context on large-scale web services

Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. Howev...

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Bibliographic Details
Main Authors: Chi-Yao Tseng, Ming-Syan Chen
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Context
Face
Face recognition
large-scale web services
Photo identity tag suggestion
real-time suggestion
social network context
Social network services
Tagging
Web services
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Description
Summary:Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. However, since the computational and storage costs of these approaches are generally high, they cannot be directly applicable to large-scale web services. To resolve this problem, we explore using only social network context to generate the top-k list of photo identity tag suggestion. The proposed method is based on various co-occurrence contexts that are related to the question of who may appear in this photo. An efficient ranking algorithm is designed to satisfy the real-time needs of this application. We utilize public album data of 400 volunteers from Facebook to verify that our approach can efficiently provide accurate suggestions with less additional storage requirement.
ISSN:1945-7871
1945-788X
DOI:10.1109/ICME.2011.6012061