No abstract

No abstract

In recent times, it has become easier to collect large quantities of customer reviews of products and services through the Internet. Thus, text-mining has become evermore important for various businesses. However, current techniques to visualize the correspondence relation between customer reviews and evaluation information are insufficient. The purpose of this paper is to propose a new method of visualizing information using a Self-organizing Map(SOM) that is robust for text data that is non-linear and multi-collinear. Our method involves, probabilistic Latent Semantic Indexing (pLSI) which does not require weighting for the dimension contraction of a word vector. Furthermore, we also propose a method to visualize the distribution of evaluation information on SOM. In order to assign a suitable value to dead nodes and nodes without evaluation values, we redefine the interpolation formula for the evaluation value. To confirm the effectiveness and accuracy of our proposal, we use our method to visualize customer review data on a major E-Commerce website.

No abstract

No abstract