A Monograph on Multimodal Semantic Information Retrieval
An Artificial Intelligent Based Ontology Approach
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Information is said to be valid and knowledgeable only if all the subjects and objects with respect to a particular domain are all arranged in a quantitative manner. To design a semantic information retrieval system, all these subjects and objects with respect to its predicate have to be defined in the given database. This can be done by Ontology Engineering. The main scope of this work is to build an intellectual multimodal semantic search framework, which has the combination of both textual semantic and visual semantics. To support the concept of multimodality, the concept of ontology is use...
Information is said to be valid and knowledgeable only if all the subjects and objects with respect to a particular domain are all arranged in a quantitative manner. To design a semantic information retrieval system, all these subjects and objects with respect to its predicate have to be defined in the given database. This can be done by Ontology Engineering. The main scope of this work is to build an intellectual multimodal semantic search framework, which has the combination of both textual semantic and visual semantics. To support the concept of multimodality, the concept of ontology is used in this research. The domain knowledge of basketball with respect to image and textual modal are integrated into an ontology. This ontology will be the backbone to a semantic search framework. Yet, to refine the search instead of providing crisp data attribute with respect to image feature, fuzzy data sets are provided. A novel procedure needs to be followed to identify the textual and image based feature vector to fill in the fuzzy ontology data attributes.
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