狂乱
发表于 2025-3-30 10:10:28
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upstart
发表于 2025-3-30 14:15:25
Towards a Proposal for a Vessel Knowledge Representation Modelthe field and for our own research efforts. It will allow easy reuse of software pieces through appropriate abstractions, facilitating the development of innovative methods, procedures and applications. In this paper we present some key ideas that will be fully developed elsewhere.
daredevil
发表于 2025-3-30 16:42:32
Developing a Probabilistic Graphical Structure from a Model of Mental-Health Clinical Risk Expertiseical structure. The Galatean Risk Screening Tool is a psychological model for mental health risk assessment based on fuzzy sets. This paper details how the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of
A简洁的
发表于 2025-3-30 22:34:26
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Fsh238
发表于 2025-3-31 01:17:48
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Acetaldehyde
发表于 2025-3-31 08:42:18
Comparing Ontologies Using Multi-agent System and Knowledge Baseacilities, like e-business, several ontologies in different languages are needed to match the users’ request. Finding the ontologies is one of the tasks, comparing and combining these ontologies is the other. The accomplishment of these tasks depends on the content in the ontologies like tags and st
蛛丝
发表于 2025-3-31 11:30:31
ACTL Local Model Update with Constraintse other hand, constraints have been playing an essential role in describing rational system behaviours. In previous model update approaches, constraints are usually not considered in the update process. In this paper, we present an ACTL - a widely used fragment of Computation Tree Logic (CTL), local
nauseate
发表于 2025-3-31 17:19:19
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石墨
发表于 2025-3-31 20:40:37
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SCORE
发表于 2025-3-31 23:25:14
Building a Framework to Design and Evaluate Meta-learning Support Systems we need to build a framework that is useful to design and evaluate meta-learning support systems. Thus we propose a framework as a basis to design and evaluate meta-learning support systems. In this paper, we firstly describe our philosophy to solve the problem. Secondly, we propose a meta-learning