Abstract
Mobile data mining is an exciting research area that aims at finding interesting patterns from datasets on mobile platform. Limited to the computing power and operating system of traditional mobile devices, mobile data mining lacks attention before. Nowadays mobile devices have a stronger and stronger computation power also the advanced operating system supporting the demand of data mining anywhere and anytime. This paper presents and implements a Java based framework to extend data mining tool Weka to mobile platform. It provides a friendly graphic user interface and simplifies the classification, clustering and associate rule mining functions on android platforms. As an example of usage, we test the model on some datasets and illustrate the feasibility of the proposed approach. A Java implementation of the model demonstrated in this article is available from mobileWeka project website. http://mobileweka.googlecode.com/files/MobileWeka.zip .
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Liu, P., Chen, Y., Tang, W., Yue, Q. (2012). Mobile WEKA as Data Mining Tool on Android. In: Xie, A., Huang, X. (eds) Advances in Electrical Engineering and Automation. Advances in Intelligent and Soft Computing, vol 139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27951-5_11
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DOI: https://doi.org/10.1007/978-3-642-27951-5_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27950-8
Online ISBN: 978-3-642-27951-5
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