Knowledge discovery of tourist subjective data in smartphone-based participatory sensing system by interactive growing hierarchical SOM and C4.5

Authors:
Takumi Ichimura;Shin Kamada;Kosuke Kato
Affiliations:
Faculty of Management and Information Systems, Prefectural University of Hiroshima, 1-1-71, Ujina-Higashi, Minami-ku, Hiroshima 731-8558, Japan.;Faculty of Management and Information Systems, Prefectural University of Hiroshima, 1-1-71, Ujina-Higashi, Minami-ku, Hiroshima 731-8558, Japan.;Faculty of Applied Information Science, Hiroshima Institute of Technology, 2-1-1 Miyake, Saeki-ku, Hiroshima 731-5193, Japan
Venue:
International Journal of Knowledge and Web Intelligence
Year:
2012

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Abstract

A self organising map (SOM) is trained using unsupervised learning to produce a two-dimensional discretised representation of input space of the training cases. Growing hierarchical SOM is an architecture which grows both in a hierarchical way representing the structure of data distribution and in a horizontal way representing the size of each individual maps. The control method of the growing degree by pruning off the redundant branch of hierarchy in SOM has been proposed and the criteria were designed by the adjustment of parameter settings according to a quantisation error and the size of map. Moreover, the interface tool for the proposed method called the interactive GHSOM has been developed. The interactive GHSOM can determine the knowledge of classification from the hierarchy of structure. A smartphone-based tourist participatory sensing system has been developed in Android smartphone. The system can collect tourist subjective data which includes jpeg files with GPS, geographic location name, the evaluation, and comments written in natural language at sightseeing spot. In this paper, we classified the subjective data by interactive GHSOM and extracted the rules by C4.5. After the interactive GHSOM implementation, the structure of the extracted rules became a lucid expression.