In this article we describe our experience in the development of a personalizable dissemination model for the Miguel de Cervantes Digital Library’s Web-based newsletter-service, which combines adaptive with adaptable personalization techniques, being capable or ranking news according to navigation-inferred preferences…

The Mediterranean Amphipoda fauna has been widely studied and can be considered one of the best known in the world (Conradi & López-González 1999); however knowledge of the fauna is not uniform throughout the entire Mediterranean, being still fragmentary on…

Web design methodologies should be able to provide a requirements analysis stage to consider the large and heterogeneous audience of Web applications. In this stage, non-functional requirements (NFRs) should be addressed in order to improve the quality of the Web…

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One important purpose for creating clinical practice guidelines is to improve quality of care by reducing variations in practice. In the current healthcare environment, guidelines are being advocated as a means to disseminate research findings, standardize care, improve quality of…

A collection of powerful ideas??cription, plans, linearity, insertions, global knowledge and imperative semantics?? explored which are fundamental to debugging skill. To make these concepts precise, a computer monitor called MYCROFT is described that can debug elementary programs for drawing pictures.…

This report concentrates on progress during the last two years at the M.I.T. Artificial Intelligence Laboratory. Topics covered include the representation of knowledge, understanding English, learning and debugging, understanding vision and productivity technology. It is stressed that these various areas…

This paper addresses the problem of recovering relative structure, in the form of an invariant, referred to as projective structure, from two views of a 3D scene. The invariant structure is computed without any prior knowledge of camera geometry, or…

This paper presents an adaptive learning model for market-making under the reinforcement learning framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. No knowledge of the market environment, such as the order…

Presented at: Conference on Structural Reform and the Transformation of Organizations and Businesses, sponsored by the Ashcroft International Business School and the Athenian Policy Forum. Homerton College, Cambridge, 3-6 September 2003.