The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the...

Purpose – The purpose of this paper is to develop an unsupervised classification algorithm including feature selection for industrial product classification with the basic philosophy of a supervised Mahalanobis‐Taguchi System (MTS). Design/methodology/approach – Two novel unsupervised...

Sentiment analysis is an important current research area. This paper combines rule-based classification, supervised learning and machine learning into a new combined method. This method is tested on movie reviews, product reviews and MySpace comments. The results show that a hybrid...

We consider the problem of mining from noisy unsupervised data sets. The data point we call noise is an outlier in the current context of data mining, and it has been generally defined as the one locates in low probability regions of an input space. The purpose of the approach for this problem...