Context-Based Semantic Tagging of Multimedia Data

With the rapid growth of broadcast systems and ease of accessing internet services, lots of information is available and accessible on the web. The information available in multimedia documents may have different context and content. Since, interpretation of multimedia content cannot be free of context so tagging on the basis on context is indispensable for dealing with this problem. Tagging plays an important role in retrieving multimedia data as now-a-days most of the videos are retrieved based on text describing them and not by the actual context embodied in them. So, in this paper we have proposed a scheme for tagging multimedia data based on the contents and context as identified from web-based resources. The hierarchical LDA (hLDA) is used to model the context information while Correspondence-LDA (Corr-LDA) is used to model the content information of multimedia data. Finally, multimedia data is tagged with the relevant contents and context information on the basis of Context-Matching Algorithm. These tags can then be used by search engines for increasing precision and recall of multimedia search results.