If such an analysis or synthesis question shall be answered automatically, both adequate algorithmic models along with the problem solving expertise of a human problem solver must be operationalized on a computer. Often, the construction of an adequate model turns out to be the key challenge when tackling the engineering task. Model construction—also known as model creation, model formation, mo...

The resource description framework (RDF) has become a formal language tool to specify the semantics of distributed systems, such as web services nowadays. In fact, it can also be extended to describe entities and relationships within specific application environments to support knowledge sharing and ontology construction. This paper presents two case studies on a network management knowledge mo...

Triple20 is an ontology manipulation and visualisation tool for languages built on top of the Semantic-Web RDF triple model. In this article we introduce a triple-centred application design and compare this design to the use of a separate proprietary internal data model. We show how to deal with the problems of such a low-level data model and show that it offers advantages when dealing with inc...

In this paper we describe a domain independent architecture to help in the design of knowledge intensive CBR systems. It is based on the knowledge incorporation from a library of application-independent ontologies and the use of an ontology with the common CBR terminology that guides the case representation and allows the description of flexible, generic and homogeneous CBR processes based on c...

In conversational case-based reasoning (CCBR), a main problem is how to select the most discriminative questions and display them to users in a natural way to alleviate users’ cognitive load. This is referred to as the question selection task. Current question selection methods are knowledge-poor, that is, only statistical metrics are taken into account. In this paper, we identify four computat...

Knowledge-intensive work plays an increasingly important role in organisations of all types. This work is characterized by a defined input and a defined output but not the way how to transform the input to an output. Within this context, the research project DYONIPOS aims at encouraging the two crucial roles in a knowledge-intensive organization the process executer and the process engineer. Ad...

In this paper we present KNOWA, an English/Italian word aligner, developed at ITC-irst, which relies mostly on information contained in bilingual dictionaries. The performances of KNOWA are compared with those of GIZA++, a state of the art statistics-based alignment algorithm. The two algorithms are evaluated on the EuroCor and MultiSemCor tasks, that is on two English/Italian publicly availabl...

In order for organizations to survive on increasingly competitive and global markets, adequate management of intellectual capital is essential. Although increasingly more information is found in electronic formats, turning this information into valuable knowledge is still the responsibility of people by applying it in professional situations to generate value. In this paper, we describe an appr...

In this paper we propose an approach to knowledge intensive CBR, where explanations are generated from a domain model consisting partly of a semantic network and partly of a Bayesian network (BN). The BN enables learning within this domain model based on the observed data. The domain model is used to focus the retrieval and reuse of past cases, as well as the indexing when learning a new case. ...