A Survey: Multimedia Content Mining Techniques using CA Based Approach

In last 10 years, there is a huge amount of multimedia data is generated by the different mediums like news agencies, social media, and other blogs. This is in the form of heterogeneous nature. Various queries to access that data are generated by the users which are based on their need and require that preference given to that data matches with the context of that query. To perform such operation a content aggregators CAs are used which are used to aggregate same type of data and predict data with respect to user query which is nearly match the user query. For this purpose a fast, accurate and efficient content aggregators are required which able to generate results with respect to users query and predict results to users query. In this paper an online learning technique is proposed in which CA is learns about users context from other CA rather than user content that make process fast and secure because there is no content is search just CA database is used to predict data as require by the user.