This paper discusses questions about communication of probabilistic knowledge in the light of current theories of agent communication. It will argue that there is a semantic gap between these theories and research areas related to probabilistic knowledge representation and communication,…

In systems where agents are required to interact with a partially known and dynamic world, sensors can be used to obtain further knowledge about the environment. However, sensors may be unreliable, that is, they may deliver wrong information (due, e.g.,…

In this paper a methodology for accesing scientific data repositories on data grids is proposed. This methodology is based on ontology specification and knowledge representation. The concept of Knowledge Perspective is introduced, as the action of applying particular scientific conjectures…

O projeto da rede corporativa de uma empresa requer que sejam bem conhecidas as características, necessidades e tendências de evolução do seu ambiente de informática, as tecnologias e tipos de equipamentos de rede disponíveis no mercado e como tais tecnologias…

Over the last several years, multidimensional data modeling has had several proposals for its formalisation; on the other hand, the incorporation of fuzzy logic in databases has increased the need to represent uncertainty.
However, to our knowledge, so far projects…

The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both…

Rough Sets Theory has opened new trends for the development of the Incomplete Information Theory. Inside this one, the notion of reduct is a very significant one, but to obtain a reduct in a decision system is an expensive computing…

This paper introduces an automatic procedure to assist on the interpretation of a large dataset when a similarity metric is available.
We propose a visualization approach based on a graph layout method- ology that uses a Quadratic Assignment Problem (QAP)…

Co-training can learn from datasets having a small number of labelled examples and a large number of unlabelled ones. It is an iterative algorithm where examples labelled in previous iterations are used to improve the classification of examples from the…

Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component…