Measuring semantic relatedness between Flickr images: from a social tag based view.
Relatedness measurement between multimedia such as images and videos plays an important role in computer vision, which is a base for many multimedia related applications including clustering, searching, recommendation, and annotation. Recently, with the explosion of social media, users can upload media data and annotate content with descriptive tags. In this paper, we aim at measuring the semantic relatedness of Flickr images. Firstly, four information theory based functions are used to measure the semantic relatedness of tags. Secondly, the integration of tags pair based on bipartite graph is proposed to remove the noise and redundancy. Thirdly, the order information of tags is added to measure the semantic relatedness, which emphasizes the tags with high positions. The data sets including 1000 images from Flickr are used to evaluate the proposed method. Two data mining tasks including clustering and searching are performed by the proposed method, which shows the effectiveness and robustness of the proposed method. Moreover, some applications such as searching and faceted exploration are introduced using the proposed method, which shows that the proposed method has broad prospects on web based tasks.
The Third Research Institute of Ministry of Public Security, 339 Bisheng Road, Shanghai 201142, China.
Zheng
Z
Xu
Shanghai University, 149 Yanchang Road, Shanghai 200472, China.
Xiangfeng
X
Luo
The Third Research Institute of Ministry of Public Security, 339 Bisheng Road, Shanghai 201142, China.
Yunhuai
Y
Liu
The Third Research Institute of Ministry of Public Security, 339 Bisheng Road, Shanghai 201142, China.
Lin
L
Mei
The Third Research Institute of Ministry of Public Security, 339 Bisheng Road, Shanghai 201142, China.
Chuanping
C
Hu
D010781:Photography; D012660:Semantics; D061108:Social Media