Using Association Link Network Model for Organizing Video Resources from Web

Zheng Xu, Xiangfeng Luo, Chen Liang, Fenglin Zhi, Lin Mei

Abstract: Recent research shows that videos "in the wild" are growing at a staggering rate. The rapid increase number of video resources has brought an urgent need to develop intelligent methods to organize the video events. In this paper, we use the Association Link Network model for organizing video resources from Web. Association Link Network is a kind of semantic link network, which is designed to establish associated relations among various resources (e.g., Web pages or documents in digital library) aiming at extending the loosely connected network of no semantics (e.g., the Web) to an association-rich network. Since the theory of cognitive science considers that the associated relations can make one resource more comprehensive to users, the motivation of ALN is to organize the associated resources loosely distributed in the Web for effectively supporting the Web intelligent activities such as browsing, knowledge discovery and publishing, etc. The tags and surrounding texts of video resources are used to represent the semantic content. The relatedness between tags and surrounding texts are implemented in the Association Link Network model. Two data sets from YouTube and Flickr1 are used to evaluate the proposed method. The experimental results show that the proposed method can measure the association relations accurately and robustly.