Basic Consideration of Online Rough C-Means Clustering and Its Application to Collaborative Filtering

Abstract

In the field of clustering, which is a technique for automatically classifying and summarizing data, rough clustering, which deals with the uncertainty of belonging to clusters by introducing a viewpoint of rough set theory, has attracted attention. Collaborative filtering based on rough clustering such as rough C-means (RCM) has been proposed and reported to be effective. However, the size of data used in a collaborative filtering task is generally very large, and it is considered to be difficult to apply conventional algorithms to the task. In this study, we propose online RCM introducing online learning and experiment with its application to collaborative filtering. Furthermore, we verify the effectiveness of the proposed method through numerical experiments using real-world datasets.