Clustering of Binary Market Research Data

Abstract

This paper details research carried out into the clustering of large market research data sets. The aim of the analysis was to find clusters of vectors in the data with maximum similarity expressed in the form of identical question answers. A novel paradigm (the interrogative memory structure) has been developed and compared with current unsupervised artificial neural network and statistical clustering techniques. The interrogative memory structure is a bi-directional network, which, when utilised with the controlling algorithm detailed in this paper, has produced encouraging results with initial tests. A detailed account of the paradigm is given along with an analysis of the initial results.