Abstract: The necessity of the mobile devices like smart phones and tabs is increasing very fast, with the advent of new technologies and the new innovations in area of communications. Even though this type of devices share a common ground exhibiting their work, but they run on different stations which makes coordination with server application. Data mining for mobile devices using web services can be made use of its best in mobile friendly environment. It improves interoperability between clients and server applications from the different platforms they execute on. Mobile user wants useful information in a short time. So that user will be able to extract relevant data. Data mining for mobile devices is very efficient process to classify data. In this paper, different types of architecture and some common tools for mobile data mining for the proposed methodology is explained. Mobile data mining is the process of extracting specific knowledge from data collected from mobile users through the different data mining techniques. As per the latest technology the status of mobile phone adoption being very high in technologically developed nations, with the expansion of mobile devices with new capabilities. With such modern mobile devices, areas that mobile users visit, time of communications, description of surrounding locations of mobile users can be collected, stored and distributed to a central location, in which it have the great potential application in area such as wholesale, retail, marketing, and banking. As the life of mobile users are mined, common patterns and knowledge such as the ordered collection of locations that they choose to visit, groups of people that they like to meet, and timing where they generally active can be collected. This supports marketing, retail and banking systems through the use of knowledge of behaviour of the mobile users. However, challenges related privacy and security are still a main constrain before the mobile user data mining can be implemented.

Keywords: Data mining, mobile devices, web services Extensible Markup Language, XML.