A Visualization Testbed for Analyzing the Performance of Computational Linguistics Algorithms
Stephen G. Eick, Justin Mauger, Alan Ratner · Information Visualization · 2007
We have built an AJAX-enabled browser-based testbed for evaluating the performance of computational linguistics algorithms. Our testbed consists of a visualization system and analysis portal. Our focus is on algorithms that classify and cluster documents by assigning weights to words and scoring each document against high-dimensional reference concept vectors. The testbed visualization and algorithm analysis techniques include Confusion Matrices, ROC Curves, Document Visualizations showing word importance, and Interactive Reports. A unique aspect of our testbed is document visualizations built using Scalable Vector Graphics that show why documents are assigned to particular concepts and categories.