Visual Data Mining for Multimedia Databases

Abstract

With computers and communication dominating technology in different fields, the need to look for media-based information processing, MBIP –rather than data-based information processing, DBIP- is increasingly being felt and this is compounded by the explosive developments in cellular communication, which brought computing and interaction on the move. The basis is to explore possibilities of using conventional data-mining approaches with visualization and object orientation so that human interaction is easier. Data Mining involves exploring databases to try and discover data relationships which are not explicitly stored with in the databases. Traditional techniques involve statistical analysis, clustering and pattern matching. Many current efforts are underway to integrate visualization in to this process. Visual data mining is a novel approach to data mining. The aim is to combine traditional data mining algorithms with information visualization techniques to utilize the advantages of both approaches. The utilization of both automatic analysis methods and human perception/understanding promises better and more effective data exploration. Visualization is a key process in visual data mining. Here the focus is on the presentation of all aspect of multimedia objects, their identification, their analysis and relationships.