Distributed classification for pocket data mining
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Context-aware collaborative data stream mining in ubiquitous devices
IDA'11 Proceedings of the 10th international conference on Advances in intelligent data analysis X
Homogeneous and heterogeneous distributed classification for pocket data mining
Transactions on Large-Scale Data- and Knowledge-Centered Systems V
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Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.