Title: Association rule mining for mobile map personalisation

Authors: Helen Zhou, Avinash Bookwala, Ruili Wang

Addresses: School of Electrical Engineering, Manukau Institute of Technology, Manukau 2240, New Zealand. ' International Telematics Ltd., Auckland, New Zealand. ' School of Engineering and Advanced Technology, College of Sciences, Massey University, Palmerston North, New Zealand

Abstract: This paper presents an algorithmic solution to map personalisation for mobile users. Fundamental data filtering approaches are combined into a working system where content-based filtering is used for regular users who have their interests/preferences profiled and collaborative filtering is used for new/occasional users without user profiles. User map interactions are implicitly collected for user profile acquisition. Furthermore, association rule mining has been applied through the user map interactions to discover the association rules for geo-spatial features/services commonly accessed together. Such association rules are stored in a tree-like data structure for efficient storing and searching. Other commonly accessed features/services can be further recommended to the personalised map by collaborative filtering. Real world datasets have been used for our system and the initial system evaluation has shown promising.

Keywords: content-based filtering; collaborative filtering; association rule mining; GIS; geographic information systems; map personalisation; mobile devices; personalised maps; user profiles; association rules.

DOI: 10.1504/IJISTA.2011.039023

International Journal of Intelligent Systems Technologies and Applications, 2011 Vol.10 No.2, pp.214 - 230

Published online: 11 Mar 2011 *

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