Searching video blogs with integration of context and content analysis

Now a day's video blogs are playing an important role. To effectively manage the vlogs and make them more conveniently accessible for users is a challenging problem. In this paper we proposed a novel vlog management model which is consists of two stages: annotation and search. In Vlog annotation, we extract informative keywords not only from the textual content of the target vlog itself but also from external resources which are semantically and visually relevant to it. Sentiment evaluation obtained from comments. In vlog search we adopt saliency based matching to make the search results. We use different ranking strategies are adapted to the user.