This paper presents a new approach for automatic document categorization. Exploiting the logical structure of the document, our approach assigns a HTML document to one or more categories (thesis, paper, call for papers, email, ...). Using a set of training documents, our approach generates a set of rules used to categorize new documents. The approach flexibility is carried out with rule weight ...

We examine the performance of dyslexic participants on an unsupervised categorization task against that of matched non-dyslexic control participants. Unsupervised categorization is a cognitive process critical for conceptual development. Existing research in dyslexia has emphasized perceptual tasks and supervised categorization tasks (for which intact attentional processes are paramount), but t...

Categorization is a primary application for conceptual knowledge stored in the human brain. Categorization is often based on similarity, involving apparent use of both prototypes and stored exemplars. Some human categorization appears to be rule or theory based rather than based on similarity. Attempts to model categorization often involve multiple subsystems to support the different observed a...

Categorization is a primary application for conceptual knowledge stored in the human brain. Categorization is often based on similarity, involving apparent use of both prototypes and stored exemplars. Some human categorization appears to be rule or theory based rather than based on similarity. Attempts to model categorization often involve multiple subsystems to support the different observed a...

Category rule learning was examined in two amnesic patients using the perceptual categorization task (e.g., Ashby & Gott, 1988; Filoteo & Maddox, 1999). Traditional accuracy-based analyses as well as quantitative model-based analyses were performed. Unlike accuracy-based analyses, the model-based approach allowed us to examine both categorization rule learning and variability in the trial-by-tr...

The evolution of color categorization is investigated using artificial agent population categorization games, by modeling observer types using Farnsworth-Munsell 100 Hue Test performance to capture human processing constraints on color categorization. Homogeneous populations of both normal and dichromat agents are separately examined. Both types of populations produce near-optimal categorizatio...

A successful text categorization experiment divides a textual collection into pre-defined classes. A true representative for each class is generally obtained during training of the categorizer. In this paper, we report on our experiments on training and categorization of optically recognized documents. In particular, we will address the issues regarding the effects OCR errors may have on traini...

Text categorization is used to automatically assign previously unseen documents to a predefined set of categories. This paper gives a short introduction into text categorization (TC), and describes the most important tasks of a text categorization system. It also focuses on Support Vector Machines (SVMs), the most popular machine learning algorithm used for TC, and gives some justification why ...

A rational model of human categorization behavior is presented that assumes that categorization reflects the derivation of optimal estimates of the probability of unseen features of objects. A Bayesian analysis is performed of what optimal estimations would be if categories formed a disjoint partitioning of the object space and if features were independently displayed within a category. This Ba...