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Full-Text Articles in Physical Sciences and Mathematics
The Round Table Model: A Web-Oriented, Agent-Based Approach To Decision-Support Applications, Kym J. Pohl, Jens G. Pohl
The Round Table Model: A Web-Oriented, Agent-Based Approach To Decision-Support Applications, Kym J. Pohl, Jens G. Pohl
Jens G. Pohl
Not unlike King Arthur relying on the infamous Round Table as the setting for consultation with his most trusted experts, agent-based, decision-support systems provide human decision makers with a means of solving complex problems through collaboration with collections of both human and computer-based expert agents. The Round Table Framework provides a formalized architecture together with a set of development and execution tools which can be utilized to design, develop, and execute agent-based, decision-support applications. Based on a three-tier architecture, Round Table incorporates forefront technologies including distributed-object servers, inference engines, and web-based presentation to provide a framework for collaborative, agent-based decision …
Learning From Labeled Features Using Generalized Expectation Criteria, Gregory Druck, Gideon Mann, Andrew Mccallum
Learning From Labeled Features Using Generalized Expectation Criteria, Gregory Druck, Gideon Mann, Andrew Mccallum
Andrew McCallum
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domain knowledge in the form of affinities between input features and classes. For example, in a baseball vs. hockey text classification problem, even without any labeled data, we know that the presence of the word puck is a strong indicator of hockey. We refer to this type of domain knowledge as a labeled feature. In this paper, we propose a method for training discriminative probabilistic models with labeled features and unlabeled …