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Collection-based sparse label propagation and its application on social group suggestion from photos

Published: 24 February 2011 Publication History

Abstract

Online social network services pose great opportunities and challenges for many research areas. In multimedia content analysis, automatic social group recommendation for images holds the promise to expand one's social network through media sharing. However, most existing techniques cannot generate satisfactory social group suggestions when the images are classified independently. In this article, we present novel methods to produce accurate suggestions of suitable social groups from a user's personal photo collection. First, an automatic clustering process is designed to estimate the group similarities, select the optimal number of clusters and categorize the social groups. Both visual content and textual annotations are integrated to generate initial predictions of the group categories for the images. Next, the relationship among images in a user's collection is modeled as a sparse graph. A collection-based sparse label propagation method is proposed to improve the group suggestions. Furthermore, the sparse graph-based collection model can be readily exploited to select the most influential and informative samples for active relevance feedback, which can be integrated with the label propagation process without the need for classifier retraining. The proposed methods have been tested on group suggestion tasks for real user collections and demonstrated superior performance over the state-of-the-art techniques.

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Published In

cover image ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology  Volume 2, Issue 2
February 2011
175 pages
ISSN:2157-6904
EISSN:2157-6912
DOI:10.1145/1899412
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 February 2011
Accepted: 01 August 2010
Revised: 01 June 2010
Received: 01 March 2010
Published in TIST Volume 2, Issue 2

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Author Tags

  1. Social image
  2. active relevance feedback
  3. collection-based sparse label propagation
  4. group recommendation

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  • (2017)Weakly Supervised Deep Matrix Factorization for Social Image UnderstandingIEEE Transactions on Image Processing10.1109/TIP.2016.262414026:1(276-288)Online publication date: 1-Jan-2017
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  • (2013)Reinforced Similarity Integration in Image-Rich Information NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2011.22825:2(448-460)Online publication date: 1-Feb-2013
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