Object Relational Similarity with Semantic Similarity for User Interactive Content based Video Retrieval from Multimedia Dataset using Semantic Ontology Vigneswaran S.*, Leelamani A.**, Divya K.*** *Research Scholar, Anna University, Regional Campus, Coimbatore, India **Assistant Professor, Anna University, Regional Campus, Coimbatore, India ***Research Fellow, Tamil Nadu Agricultural University, Coimbatore, India Online published on 2 August, 2016. Abstract This chapter is about retrieval of video from large set of multimedia data set. In general the video retrieval is performed based on the contextual information. For example, if the user requests the video in which Dhoni plays football, it returns the set of video files, which contains the dhoni playing cricket or dhoni playing all games. Such irrelevancy in results is higher in the previous search mechanism. So in order to improve the efficiency of video retrieval, the object relational similarity is computed on the video content present in each class. Similarly the method computes the semantic similarity for the different class of multimedia content. Based on both the similarity measure the method ranks the results and produce to the user. The user is allowed to refine their query and based on the query provided the method refine the result or research the query. The method produces efficient result in interactive multimedia search and reduces the false ratio. Top Keywords Content Retrieval, Multimedia, Object mapping, Semantic Ontology, Video retrieval, Interactive. Top |