SenMinCom: Pervasive Distributed Dynamic Sensor Data Mining for Effective Commerce

• Main Author: Hiremath, Naveen
• Format: Others
• Published: Digital Archive @ GSU 2008
• Subjects: real time shopping information; commerce; mobile agent; distributed pervasive mining; dynamic data mining; wireless sensor network; Computer Sciences
• Online Access: http://digitalarchive.gsu.edu/cs_theses/55; http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1054&context=cs_theses

In last few years, the use of wireless sensor networks and cell phones has become ubiquitous; fusing these technologies in the field of business will open up new possibilities. To fill this lacuna, I propose a novel idea where the combination of these will facilitate companies to receive feedback on their products and services. System's unobtrusive sensors will not only collect shopping, mobile usage data from consumers but will also make effective use of this information to increase revenue, cut costs, etc.; the use of mobile agent based data mining allows analyzing the data from different dimensions, categorizing it on factors such as product positioning, promotion of goods, etc. as in the case of a shopping store. Additionally, because of the dynamic mining system the companies get on-the-scene recommendation of products rather than off-the-scene. In this thesis, a novel distributed pervasive mining system is proposed to get dynamic shopping information and mobile device usage of the customers.