Late Semantic Fusion Approaches for Multimedia Information Retrieval with Automatic Tag Generation

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retrieval in general and content based image retrieval in particular are well known research fields in information retrieval management. An image contains several types of visual information which are difficult to extract and combine manually by humans. The main goal of this paper is to show multimedia information retrieval task using the combination of textual pre-filtering and image re-ranking. The combination of textual and visual techniques and retrieval processes used to develop the multimedia information retrieval system by which we solves the problem of the semantic gap of the given query. Five late semantic fusion approaches are used for text based and content based image retrieval of any dataset. The logistic regression relevance feedback algorithm is used to determine the similarity between the images from the dataset to the query.