Discovery of Associated Topics for the Intelligent Browsing

Intelligent browsing of topics is one of the key issues of the Web and the Knowledge Grid, which provides on-demand services to support knowledge discovery and innovation. In this paper, Background of topics composed by Associated Relations (BAR) between keywords belonging to one domain is developed to extend the topics' associated relations based on the Element Fuzzy Cognitive Maps (E-FCMs), which helps us discover the associated topics that do not have direct associated relation at the keyword level. The Matrix of element Concepts (MC) is presented to store element concepts of topics. Through MC we can obtain the causal concepts of each topic in one domain; logic operation "AND" is given to get associated topics. Semantic Link Network (SLN) is automatically generated by the associated topics, which can realize the intelligent browsing of topics in Web or Knowledge Grid. Experimental results show that the browsing path of topics is easier to be built by the proposed algorithm and the associated topic can be recommended automatically. Meanwhile, an application of the associated topics in multimedia provides a good prospect on the cross media intelligent browsing.