A semantic-based model to represent multimedia big data
Antonio M. Rinaldi, Cristiano Russo · 2018
The use of formal representation is a key task in the era of big data. In the context of multimedia big data this issue is stressed due to the intrinsic complexity nature of this kind of data. Moreover, the relations among objects should be clearly expressed and formalized to give the right meaning of data correlation. For this reason the design of formal models to represent and manage information is a necessary task to implement intelligent information systems. In this latter some approaches related to the semantic web could be used to improve the data models which underlie the implementation of big data applications. Using these models the visualization of data and information become an intrinsic and strategic task for the analysis and exploration of multimedia BigData. In this paper we propose the use of a semantic approach to formalize the model structure of multimedia BigData. In addition, the recognition of multimodal features to represent concepts and linguistic properties to relate them are an effective way to bridge the gap between the target semantic classes and the available low-level multimedia descriptors. The proposed model has been implemented in a NoSQL graph database populated from different knowledge sources and a visualization of this very large knowledge base has been presented and discussed as a case study.