An in-device, real-time mining of data on a ubiquitous computing environment in accordance to the environment’s requirements by considering resource constraints of the device, exploiting context information, behaving autonomously and applying special privacy preserving methods.
Published in Chapter:
Research Challenge of Locally Computed Ubiquitous Data Mining
Aysegul Cayci (Sabanci University, Turkey), João Bártolo Gomes (Universitad Politecnica, Spain), Andrea Zanda (Universitad Politecnica, Spain), Ernestina Menasalvas (Universitad Politecnica, Spain), and Santiago Eibe (Universitad Politecnica, Spain)
Copyright: © 2011
|Pages: 19
DOI: 10.4018/978-1-60960-042-6.ch037
Abstract
Advances in wireless, sensor, mobile and wearable technologies present new challenges for data mining research on providing mobile applications with intelligence. Autonomy and adaptability requirements are the two most important challenges for data mining in this new environment. In this chapter, in order to encourage the researchers on this area, we analyzed the challenges of designing ubiquitous data mining services by examining the issues and problems while paying special attention to context and resource awareness. We focused on the autonomous execution of a data mining algorithm and analyzed the situational factors that influence the quality of the result. Already existing solutions in this area and future directions of research are also covered in this chapter.