Surveillance video recording is becoming ubiquitous in daily life for public areas such as supermarkets, banks, and airports. The rate at which surveillance video is being generated has accelerated demand for machine understanding to enable better content-based search capabilities. Analyzing human activity is one of the key tasks to understand and…

In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…

Although a variety of studies have indicated that using statistical clustering techniques to examine genetic information may allow for geographically based groupings of individuals that tenuously map onto some conceptions of race, these studies have also indicated that the amount of genetic variation within these groupings is significantly larger…

Graphical methods for evaluating the fit of Johnson's hierarchical clustering schemes are presented together with an example. These evaluation methods examine the extent to which the clustering algorithm can minimize the overlap of the distributions of intracluster and intercluster distances. (Author)

A method is described for bifurcating a matrix of objects into two submatrices such that the sum of average deviations of the members from the central tendencies of the two submatrices is minimized. Illustrations of the procedure are included. (DG)

Dissimilarity Linkage Analysis (DLA) is an extremely simple procedure for developing a typology from empirical attributes that permits the clustering of entities. First the procedure develops a taxonomy of types from empirical attributes possessed by entities in the sample. Second, the procedure assigns entities to one, and only one, type in the…

Recent trends in the analysis of categorical or nominal variables were discussed for univariate, multivariate, and psychometric problems. It was shown that several statistical procedures commonly used with these problems have analogues which can be applied to assessing categorical variables. (Author/CTM)

Clustering techniques seek to group together objects or variables that share some observed qualities or, alternatively, to partition a set of objects or variables into mutually exclusive classes whose boundaries reflect differences in the observed qualities of their members. This paper reviews the general principles underlying clustering…

"Classification: Purposes, Principles, Progress, Prospects" by Robert R. Sokal is reprinted in this document. It summarizes the principles of classification and cluster analysis in a manner which is of specific value to the Marine Corps Office of Manpower Utilization. Following the article is a 184 item bibliography on cluster analysis…

A class of closely related hierarchical grouping methods are discussed and a procedure which implements them in an integrated fashion is presented. These methods avoid some theoretical anomalies inherent in clustering and provide a framework for viewing partitioning and nonpartitioning grouping. Significant relationships between these methods and…

The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…

A cluster analytic study was conducted to derive behaviorally homogeneous subtypes of pervasive developmental disorders (PDD) based on a range of behavioral symptoms that characterize autism. Analysis of data on 34 children with PDD, 27 of whom met criteria for autism, indicated 4 distinct groups differing on independent measures of social,…

The purpose of this paper is to suggest a technique of cluster analysis which is similar in aim to the Interactive Intercolumnar Correlation Analysis (IICA), though different in detail. Two methods are proposed for extracting a single bipolar factor (a "contrast compenent") directly from the initial similarities matrix. The advantages of this…