Title: A granular hardware/software system: pervasive distributed dynamic sensor data mining system for effective commerce
Author: Naveen Hiremath, Yan-Qing Zhang
Department of Computer Science, Georgia State University, Atlanta, GA 30302-3994, USA.
Department of Computer Science, Georgia State University, Atlanta, GA 30302-3994, USA
Abstract: In recent years, wireless sensor networks, cell phones and granular hardware/software systems have become ubiquitous for various applications; fusing these technologies in the field of business opens up new applications. To fill this lacuna, we propose a novel idea where the combination of these technologies facilitates the stores to receive feedback on their products and services. System's unobtrusive sensors will not only collect shopping data from customers, but will also make effective use of this information to increase revenue, cut costs, etc.; the use of mobile agents-based data mining allows analysing the data from different dimensions and categorising it on factors such as product positioning, promotion of goods, etc. Additionally, the shoppers get on-the-scene recommendation of products, rather than off-the-scene. In this paper, a novel granular distributed pervasive mining system is proposed to get dynamic shopping information of the customers.
Keywords: granular hardware; granular software; granular computing; wireless sensor networks; WSNs; data mining; mobile agents; e-commerce; wireless networks; cell phones; mobile phones; sensors; agent-based systems; multi-agent systems; electronic commerce; shopping data; online shopping; product recommendations; recommender systems.
Int. J. of Granular Computing, Rough Sets and Intelligent Systems, 2010 Vol.1, No.3, pp.252 - 271
Available online: 30 Nov 2009