Research on knowledge representation, machine learning, and knowledge acquisition

Research in knowledge representation, machine learning, and knowledge acquisition performed at Knowledge Systems Lab. is summarized. The major goal of the research was to develop flexible, effective methods for representing the qualitative knowledge necessary for solving large problems that require symbolic reasoning as well as numerical computation. The research focused on integrating different representation methods to describe different kinds of knowledge more effectively than any one method can alone. In particular, emphasis was placed on representing and using spatial information about three dimensional objects and constraints on the arrangement of these objects in space. Another major theme is the development of robust machine learning programs that can be integrated with a variety of intelligent systems. To achieve this goal, learning methods were designed, implemented and experimented within several different problem solving environments

Vaccine Risk Communication: Lessons from Risk Perception, Decision Making and Environmental Risk Communication Research

Dr. Bostrom reviews the rich variety of empirical findings available to guide risk communication and demonstrates how it can contribute to vaccine risk and safety communication

A systematic review of software development cost estimation studies

This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods

Applying case based reasoning for prioritizing areas of business management

Determining the importance of different management areas in a company provides guidance about the needs of increasing the analysis and actions focuses in particular topic. To do it, it is necessary to decompose the management in a coherent set of specific management areas and provide a way that allows the company to determine the importance of these areas for them. This paper presents a novel system that guides companies to obtain a classification of important management areas for them. It is focused on the use of a case based reasoning system because the variability and the evolution of companies as time passes requires using techniques with learning capabilities. The proposed system provides an automatic self-assessment system that provides companies an ordered list of their most important management areas. This system was implemented a year ago for the evaluation of Spanish companies. Currently, it is in production providing relevant information about the management areas of these companies

Systems for technical refinement in experienced performers: The case from expert-level golf

This paper provides an overview of current golf coaching practices employed with experts, when attempting to make changes to (i.e., refine) a player’s existing technique. In the first of two studies, European Tour golfers (n = 5) and coaches (n = 5) were interviewed to establish the prevalence of any systematic processes, and whether facilitation of resistance to competitive pressure (hereafter termed “pressure resistance”) was included. Study 2 employed an online survey, administered to 89 PGA Professionals and amateur golfers (mostly amateurs; n = 83). Overall, results suggested no standardized, systematic, or theoretically considered approach to implementing technical change, with pressure resistance being considered outside of the change process itself; if addressed at all. In conclusion, there is great scope for PGA professionals to increase their coaching efficacy relating to skill refinement; however, this appears most likely to be achieved through a collaborative approach between coach education providers, researchers, and coaches

The Clinical Assessment in the Legal Field: An Empirical Study of Bias and Limitations in Forensic Expertise

According to the literature, psychological assessment in forensic contexts is one of the most controversial application areas for clinical psychology. This paper presents a review of systematic judgment errors in the forensic field. Forty-six psychological reports written by psychologists, court consultants, have been analyzed with content analysis to identify typical judgment errors related to the following areas: (a) distortions in the attribution of causality, (b) inferential errors, and (c) epistemological inconsistencies. Results indicated that systematic errors of judgment, usually referred also as "the man in the street," are widely present in the forensic evaluations of specialist consultants. Clinical and practical implications are taken into account. This article could lead to significant benefits for clinical psychologists who want to deal with this sensitive issue and are interested in improving the quality of their contribution to the justice system