Soft multi-modal data fusion

Abstract

Clustering groups items together that are most similar to each other and sets those that are least similar into different clusters. Methods have been developed to cluster records in a data set that are of only qualitative or quantitative data. Data sets exist that contain a mix of qualitative (nominal and ordinal) and quantitative (discrete and continuous) data. Clustering records of mixed kinds of data is a difficult problem. A metric to measure the similarity between records of mixed data types is needed. Once a clustering is found, we do not know how to best evaluate the quality of the clustering when there is a mixture of data varieties.