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ICCBR
2005
Springer
14 years 5 months ago
Learning Semantic Annotations for Textual Cases
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
Eni Mustafaraj, Martin Hoof, Bernd Freisleben
ICCBR
2005
Springer
14 years 5 months ago
Abstracting Reusable Cases from Reinforcement Learning
Andreas von Hessling, Ashok K. Goel
ICCBR
2005
Springer
14 years 5 months ago
Re-using Implicit Knowledge in Short-Term Information Profiles for Context-Sensitive Tasks
Typically, case-based recommender systems recommend single items to the on-line customer. In this paper we introduce the idea of recommending a user-defined collection of items whe...
Conor Hayes, Paolo Avesani, Emiliano Baldo, Padrai...
ICCBR
2005
Springer
14 years 5 months ago
Game-Based Learning as a New Domain for Case-Based Reasoning
Tutoring systems have been a popular domain for CBR since its very beginning. In this paper we draw a connection between casebased teaching and learning-by-doing approach to tutori...
Marco Antonio Gómez-Martín, Pedro Pa...
ICCBR
2005
Springer
14 years 5 months ago
Opportunities for CBR in Learning by Doing
In this paper we partially describe JV2 M, a metaphorical simulation of the Java Virtual Machine where students can learn Java language compilation and reinforce object-oriented pr...
Pedro Pablo Gómez-Martín, Marco Anto...
ICCBR
2005
Springer
14 years 5 months ago
Supporting Conversation Variability in COBBER Using Causal Loops
Conversational Case Based Reasoning (CCBR) is a form of CBR where users initiate conversations with the system to solve a certain problem. Current CCBR solutions are limited to spe...
Hector Gómez-Gauchía, Belén D...
ICCBR
2005
Springer
14 years 5 months ago
Reasoning with Textual Cases
Stefanie Brüninghaus, Kevin D. Ashley
ICCBR
2005
Springer
14 years 5 months ago
CBR for State Value Function Approximation in Reinforcement Learning
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...
Thomas Gabel, Martin A. Riedmiller
ICCBR
2005
Springer
14 years 5 months ago
P2P Case Retrieval with an Unspecified Ontology
Traditional CBR approaches imply centralized storage of the case base and, most of them, the retrieval of similar cases by an exhaustive comparison of the case to be solved with th...
Shlomo Berkovsky, Tsvi Kuflik, Francesco Ricci
ICCBR
2005
Springer
14 years 5 months ago
Evaluation and Monitoring of the Air-Sea Interaction Using a CBR-Agents Approach
This paper presents a model constructed for the evaluation of the interaction of the atmosphere and the ocean. The work here presented focuses in the development of an agent based ...
Javier Bajo, Juan M. Corchado