Sciweavers

Share
IFIP12
2008
8 years 12 months ago
Agent Based Frequent Set Meta Mining: Introducing EMADS
In this paper we: introduce EMADS, the Extendible Multi-Agent Data mining System, to support the dynamic creation of communities of data mining agents; explore the capabilities of ...
Kamal Ali Albashiri, Frans Coenen, Paul H. Leng
IFIP12
2008
8 years 12 months ago
A Risk Assessment System with Automatic Extraction of Event Types
In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, ...
Philippe Capet, Thomas Delavallade, Takuya Nakamur...
IFIP12
2008
8 years 12 months ago
Addressing Risk Assessment for Patient Safety in Hospitals through Information Extraction in Medical Reports
: Hospital Acquired Infections (HAI) is a real burden for doctors and risk surveillance experts. The impact on patients' health and related healthcare cost is very significant...
Denys Proux, Frédérique Segond, Solw...
IFIP12
2008
8 years 12 months ago
Making Others Believe What They Want
We study the interplay between argumentation and belief revision within the MAS framework. When an agent uses an argument to persuade another one, he must consider not only the pro...
Guido Boella, Célia da Costa Pereira, Andre...
IFIP12
2008
8 years 12 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
IFIP12
2008
8 years 12 months ago
Optimizing Relationships Information in Repertory Grids
The Repertory Grid method is widely used in knowledge engineering to infer functional relationships between constructs given by an expert. The method is ignoring information that c...
Enrique Calot, Paola Britos, Ramón Garc&iac...
IFIP12
2008
8 years 12 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...
IFIP12
2008
8 years 12 months ago
Teaching Autonomous Agents to Move in a Believable Manner within Virtual Institutions
Believability of computerised agents is a growing area of research. This paper is focused on one aspect of believability - believable movements of avatars in normative 3D Virtual W...
Anton Bogdanovych, Simeon J. Simoff, Marc Esteva, ...
IFIP12
2008
8 years 12 months ago
A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System
Sampling methods are a direct approach to tackle the problem of class imbalance. These methods sample a data set in order to alter the class distributions. Usually these methods ar...
Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Mar...
books