Artificial Intelligent Techniques for Wireless Communication and Networking

11Class Level Multi-Feature Semantic Similarity-Based Efficient Multimedia Big Data Retrieval

D. Sujatha¹, M. Subramaniam^2* and A. Kathirvel³

¹DCSE, St. Peters College of Engineering and Technology, Chennai, India

²Dept. of Information Technology, Sree Vidyanikethan Engineering College, Sree Sainath Nagar, Tirupati, Andhra Pradesh, India

³Dept. of CSE, Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore, Tamil Nadu, India

Abstract

The development of information technology has given different dimensions for the form of data and has opened the gate to manage data in different ways. Earlier days involved data management in a basic way as they were classified simply. The technology development in information management opened the gate for the users to combine various relational data to form a single entity. This increased the phenomenon of combining various personal details to form a big data. Storage and retrieval of multimedia big data has been handled with several techniques based on different features. The number of approaches has been discussed earlier but suffers to achieve higher performance in big data retrieval. To solve this issue, an efficient class level multi-feature semantic similarity measure based approach has been presented in this paper. The method receives the input query and estimates class level information similarity, class level texture similarity, class level semantic similarity measure for different classes. Using these measures, the ...