Abstract-This article presents a middle-out approach to build legal domain reference ontology for a Legal Knowledge Based System (LKBS). The proposed approach is a combination of top-down and bottom-up strategies. In particular, we propose to develop legal domain reference ontology, splitted into modules or fragments, based on merging two processes: Conceptual Modeling Process, by reusing foundational ontologies (top-down strategy) and Ontology Learning Process from textual resources (bottom-up strategy).Index Terms-Conceptual modeling, domain reference ontology, legal ontology, modularization, ontology learning.
This paper describes a work currently in progress whose aim is to design. develop and evaluate a Multi-Agent Framework for Data Fusion (DFMAF). This is being done with the support of a battlefield surveillance demonstrator application, named TA-b [3.61. Through the following chapters. we will describe the benefits of using such a framework for data fusion problems. Firstly. we will briefly present the multi-agent research domain. Then, we will go into further details to describe DFMAF. the multi-agent framework designed to help solving data fusion problems. The appropriateness of DFMAF to data fusion problems will also he pointed out. Next, the implementation and use of DFMAF in the support application will he detailed as well as the assessment procedure followed. Finally, we will conclude and expose the future work which will he done.
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