Teleimmersive environment for collaborative visual data mining

VidaMine: a visual data mining environment

That the already vast and ever-increasing amounts of data still do present formidable challenges to effective and efficient acquisition of knowledge is by no means an exaggeration. The knowledge discovery process entails more than just the application of data mining strategies. There are many other aspects including, but not limited to: planning, data preprocessing, data integration, evaluation...

Visual Data Mining Framework for Video Data

With advances in computing techniques, a large amount of high resolution high-quality multimedia data (video and audio, etc.) has been collected in research laboratories in various scientific disciplines, particularly in social and behavioral studies. How to automatically and effectively discover new knowledge from rich multimedia data poses a compelling challenge since state-oftheart data mini...

Meta Data for Visual Data Mining

Increasing amounts of large data and information sets require new analysis techniques. The domain of data mining investigates new paradigms and methods adapted for scalability, flexibility and problem abstraction for large data sets. In particular the field of visual data mining offers valuable methods for analyzing large amount of data intuitively. Visual data mining combines several visual an...

Collaborative Data Mining Tool for Education

An Architecture for Collaborative Data Mining

Collaborative Data Mining (CDM) develops techniques to solve complex problems of data analysis requiring sets of experts in different domains that may be geographically separate. An important issue in CDM is the sharing of experience among the different experts. In this paper we report on a framework that enables users with different expertise to perform data analysis activities and profit, in ...