Rita Temmerman

Towards new ways of terminology description : the sociocognitive-approach

Based on an empirical study of categorisation and lexicalisation processes in a corpus of scientific publications on the life sciences, Rita Temmerman questions the validity of traditional terminology theory. Her findings are that the traditional approach impedes a pragmatic and realistic description of a large number of categories and terms. Inspired by the cognitive sciences, she develops an alternative. The main principles of this new theory imply: a combined semasiological and onomasiological perspective; only few categories can be clearly delineated; form and content of definitions vary according to category types and users requirements; synonymy and polysemy are functional in special language and a diachronic approach is unavoidable. This last principle implies the varying importance of historical information in definitions, the non-arbitrariness of lexicalisation and the importance of cognitive models. In a last chapter the author shows how the methods and principles of the alternative approach are applicable in terminography and how this is going to have an impact on software for terminological database construction. This book will be valuable for specialists in terminology theory, practising terminographers and for anybody interested in special language, cognitive models and prototype theory.

Towards Ontology-based E-mail Fraud Detection

The European FF POIROT project (IST-2001-38248) aims at developing applications for tackling financial fraud, using formal ontological repositories as well as multilingual terminological resources. In this article, we want to focus on the development cycle towards an application recognizing several types of e-mail fraud, such as phishing, Nigerian advance fee fraud and lottery scam. The development cycle covers four tracks of development - language engineering, terminology engineering, knowledge engineering and system engineering. These development tracks are preceded by a problem determination phase and followed by a deployment phase. Each development track is supported by a methodology. All methodologies and phases in the development cycle will be discussed in detail

Engineering an Ontology of Financial Securities Fraud

This paper discusses the approach of ontology-based knowledge engineering in FF POIROT, a project to explore the use of ontology technology in information systems against financial fraud. A fraud forensic ontology is being developed from laws, regulations and cases about illegal solicitation of financial products on the web. The knowledge development is based on the DOGMA ontology paradigm, and the derived ontology engineering methodology AKEM. The regulatory ontology engineering is a multi-disciplinary and distributed team work through a series of tasks and deliverables with emphasis on the traceability of decision making in the development. The machine ontology extraction and a manually constructed bilingual terminological database, is used to support the ontology modelling process.

Facilitating ontology (re)use by means of a categorization framework

Ontologies as means for conceptualizing and structuring domain knowledge within a community of interest are seen as a key to realize the Semantic Web vision However, the decentralized nature of the Web makes achieving consensus across communities difficult, thus, hampering efficient knowledge sharing between them To address this problem of heterogeneity we propose a Categorization Framework (CF) that makes it possible to use (multilingual) terminology to specify concepts and concept relations in domain ontologies Such CF could describe the meaning of concepts and concept relations by means of terminological information and external references We believe that such (multilingual) ontology description could enhance the (re)usability and facilitate the coordination of domain ontologies.

Termontography and DOGMA for Knowledge Engineering within PROLIX

In this article, we describe our ongoing research to combine two approaches, i.e. Termontography and DOGMA, for knowledge engineering. Both approaches have in common that they mainly rely on natural language to describe meaning. Termontography is a special form of terminography that results in an ontologically structured terminological resource. DOGMA is an abbreviation of Developing Ontology Guided Mediation for Agents. The DOGMA approach results in a scalable and modular ontology that can easily be (re)used for different domains and applications. Both Termontography and DOGMA have already been used separately during several research projects. In this article we explain how both approaches are being combined within the PROLIX project, and what the advantages of this combination are. The goal of PROLIX is to develop an open, integrated reference architecture for process-oriented learning and information exchange.

Asking the Right Question: How to Transform Multilingual Unstructured Data to Query Semantic Databases

Ontology engineers have long tried to develop mechanisms to automatically transform natural language statements into queries knowledge-systems can deal with. This has been an enormous challenge as natural languages are highly ambiguous and contexts for disambiguating are seldom identifiable through simple linguistic patterns. To circumvent these difficulties, developers of knowledge bases have often opted for the use of a restricted vocabulary and syntax. Normal users, nevertheless, prefer to express themselves in their language. Special languages or schemas tend to reflect one language – the developer’s – and make extensibility more difficult. Also multilingual access can be more difficult to handle in that way. In this article we present strategies for transforming queries of natural languages into language-neutral representations that can be more easily transformed into semantic queries. We describe a tool that combines a multilingual database and natural processing modules with a semantic database in order to transform queries in Dutch, French and English into queries from which ambiguity at syntactic and semantic levels have been reduced. We focus on certain aspects of natural language such as negation and collocation preferences to deal with semantics.