MultiMICS: a contextual multifaceted intelligent multimedia information fusion paradigm

Accomplishment in various aspects of life is associated with the balanced intelligence of human beings. Intelligence can be classified into several types, each of them has an influence on one’s individual and activity-related outcomes. Depending on the previous literature on intelligent systems, this article intends to trace the evolution of diverging types of multifaceted and multiple computational intelligence in the context of multimedia information framework; right from cognitive intelligence to naturalistic intelligence. We have illustrated a systematic schema of how the multiple and mutually exclusive intelligence categories affect the structural information processing phenomena. We have depicted a set of contextual case studies over the multimedia information patterns, such as images, linguistics, and music to enhance the capability of learning and representation. Thereby, distinctive characteristics of intelligence suggestively influence the entire multimedia information fusion schema in terms of multimedia pattern analysis, information retrieval, and recommendations. We have incorporated three diverge and semantic case studies for demonstrating the multifaceted intelligent information fusion on the multimedia contents such as (a) facial recognition system for auto-generated response management, (b) speech recognition module for response management and interactive system demonstration, and (c) music processing schema for illustrating pervasive music teaching–learning framework. We have evaluated the performance metrics for each of the three demonstrated case studies. The appraised outcome shows that our projected multimedia module-based information processing paradigm provides efficient system manifestation and is effectively capable of signifying multifaceted intelligent computing systems.