Defenses against adversarial attacks are essential to ensure the reliability of machine learning models as their applications are expanding in different domains. Existing ML defense techniques have several limitations in practical use. I proposed a trustworthy framework that employs an adaptive strategy to inspect both inputs and decisions. In…

Recommender systems aim to support users in their decision-making process while interacting with large information spaces and recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems are increasingly used with product and service selection over the Internet. Although…

Leveraging the knowledge of an organization is an ongoing challenge that has given rise to the field of knowledge management. Yet, despite spending enormous sums of organizational resources on Information Technology (IT) systems, executives recognize there is much more knowledge to harvest. Prediction markets are emerging as one tool to help…

Clinically oriented computer systems require compatibility with the information processing that typifies clinical work. This paper summarizes some of the research that can be applied to such processing and uses the summary to suggest likely errors. Emphasis is placed on decision support systems that integrate human and computer information…

Satisfaction is a construct that is important to the development of intrinsic motivation and the continuing effort to learn. Research that helps to identify those factors that contribute to satisfaction is useful in the design of electronic support systems for individuals and groups. This paper investigates the impact of "need for…

Universities must achieve a new maturity in institutional planning and information management to meet the challenges of the 1980s. Decision support systems are analyzed and those that combine computing technology with knowledge about decision-making art found to hold the most promise. (Author/MLW)