2014 Volume 65 Issue 3 Pages 180-190
Recently, it has become easy to collect large volumes of customers' voice through the web as text data. Accordingly, the role of text mining has become more and more important for various business situations to obtain useful knowledge easily and in large quantities. However, the technique of visualizing the correspondence relation between customer reviews and evaluation information is insufficient. The purpose of this paper is to propose a new method of visualizing the information from the text data of a customer review using a self-organizing map robust for non-linearity and multi-collinearity. In this proposal, probabilistic latent semantic indexing, which does not require weighting for dimension contraction of a word vector, was used. Furthermore, the method of visualizing the distribution of evaluation information in a self-organizing map is newly proposed. Here, in order to give a suitable value to the nodes without an evaluation value and the dead nodes, an interpolation formula for the evaluation value was newly defined. To confirm the validity of our proposal, we visualized the customer review data in a major electronic commerce site using the proposed method.
