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research-article

Tri-Clustered Tensor Completion for Social-Aware Image Tag Refinement

Published: 01 August 2017 Publication History

Abstract

Social image tag refinement, which aims to improve tag quality by automatically completing the missing tags and rectifying the noise-corrupted ones, is an essential component for social image search. Conventional approaches mainly focus on exploring the visual and tag information, without considering the user information, which often reveals important hints on the (in)correct tags of social images. Towards this end, we propose a novel tri-clustered tensor completion framework to collaboratively explore these three kinds of information to improve the performance of social image tag refinement. Specifically, the inter-relations among users, images and tags are modeled by a tensor, and the intra-relations between users, images and tags are explored by three regularizations respectively. To address the challenges of the super-sparse and large-scale tensor factorization that demands expensive computing and memory cost, we propose a novel tri-clustering method to divide the tensor into a certain number of sub-tensors by simultaneously clustering users, images and tags into a bunch of tri-clusters. And then we investigate two strategies to complete these sub-tensors by considering (in)dependence between the sub-tensors. Experimental results on a real-world social image database demonstrate the superiority of the proposed method compared with the state-of-the-art methods.

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        cover image IEEE Transactions on Pattern Analysis and Machine Intelligence
        IEEE Transactions on Pattern Analysis and Machine Intelligence  Volume 39, Issue 8
        Aug. 2017
        208 pages

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        IEEE Computer Society

        United States

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        Published: 01 August 2017

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        • (2024)A Progressive Skip Reasoning Fusion Method for Multi-Modal ClassificationProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681437(429-437)Online publication date: 28-Oct-2024
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