We propose a novel two-view learning framework for social tag ranking, which is purely data-driven without making any assumption on modeling the relationship.
In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view ...
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In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view.
In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view ...
Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could ...
This paper aims to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel ...
In this paper, we aim to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two ...
It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the ...
Nov 1, 2015 · In the proposed method, each ranked tag list is decomposed into a number of image–tag pairs, all of which are pooled together for training a ...
Zhuang, J.F., Hoi, S.C.H.: A two-view learning approach for image tag ranking. ... tag relevance for image tag re-ranking. In: Proceedings of SIGIR 2012 ...