Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions…

Reviews visualization techniques for scientific disciplines and information retrieval and classification. Highlights include historical background of scientometrics, bibliometrics, and citation analysis; map generation; process flow of visualizing knowledge domains; measures and similarity calculations; vector space model; factor analysis;…