Clustering Algorithm

A clustering algorithm is an unsupervised machine-learning technique that groups similar data points together based on a distance or similarity measure, without needing pre-labelled training data. Common algorithms include K-means, PAM (Partitioning Around Medoids), CLARA (Clustering LARge Applications), hierarchical clustering, and DBSCAN. In accessibility research, clustering algorithms are used to group pages by their error profile for stratified sampling, to identify patterns of user behaviour in assistive-technology usage logs, to cluster users by disability profile in co-design studies, and to group similar accessibility issues for triage in automated testing.