Peter Spyns

OntoWeb - A Semantic Web Community Portal

This paper describes a semantic portal through which knowledge can be gathered, stored, secured and accessed by members of a certain community. In particular, this portal takes into account companies and research institutes participating in the E.U. funded thematic network called OntoWeb. Ontology-based annotation of information is a prerequisite in order to offer the possibility of knowledge retrieval and extraction. The usage of well-defined semantics allows for the knowledge exchange between different OntoWeb community members. Thus, members are able to publish annotated information on the web, which is then crawled by a syndicator and stored in the portals knowledge base. The backbone of the portal architecture consists of a knowledge base in which the ontology and the instances are stored and maintained. In addition, ontology-boosted query mechanisms and presentation facilities are provided.

An ontology engineering methodology for DOGMA

Although ontologies occupy a central place in the Semantic Web and related research domains, there are currently not many fully fledged ontology engineering methodologies available. In this paper, we want to present an integrated methodology for ontology engineering from scratch, inspired by various scientific disciplines, in particular database semantics and natural language processing.

Automatic Initiation of an Ontology

We report on an a set of experiments carried out in the context of the Flemish OntoBasis project. Our purpose is to extract semantic relations from text corpora in an unsupervised way and use the output as preprocessed material for the construction of ontologies from scratch. The experiments are evaluated in a quantitative and ”impressionistic” manner.

Lexically evaluating ontology triples generated automatically from texts

Our purpose is to present a method to lexically evaluate the results of extracting in an unsupervised way material from text corpora to build ontologies. We have worked on a legal corpus (EU VAT directive) consisting of 43K words. The unsupervised text miner has produced a set of triples. These are to be used as preprocessed material for the construction of ontologies from scratch. A quantitative scoring method (coverage, accuracy, recall and precision metrics resulting in a 38.68%, 52.1%, 9.84% and 75.81% scores respectively) has been defined and applied.

Viewpoints on emergent semantics

We introduce a novel view on how to deal with the problems of semantic interoperability in distributed systems. This view is based on the concept of emergent semantics, which sees both the representation of semantics and the discovery of the proper interpretation of symbols as the result of a self-organizing process performed by distributed agents exchanging symbols and having utilities dependent on the proper interpretation of the symbols. This is a complex systems perspective on the problem of dealing with semantics. We highlight some of the distinctive features of our vision and point out preliminary examples of its application.

Creating a “DOGMAtic” Multilingual Ontology Infrastructure to Support a Semantic Portal

We present extensions to the current DOGMA ontology engineering framework so that the DOGMA ontology server is better equiped to cope with context and multilinguality, issues that are important when deploying “ontology technology” in a setting involving human users. An obvious example is a semantic portal that offers search facilities to its users. A short presentation of the DOGMA ontology engineering approach will be provided, before the extensions mentioned will be presented.

Object role modelling for ontology engineering in the DOGMA framework

A recent evolution in the areas of artificial intelligence, database semantics and information systems is the advent of the Semantic Web that requires software agents and web services exchanging meaningful and unambiguous messages. A prerequisite for this kind of interoperability is the usage of an ontology. Currently, not many ontology engineering methodologies exist. This paper describes some basic issues to be taken into account when using the ORM methodology for ontology engineering from the DOGMA ontology framework point of view.

Mining for Lexons: Applying Unsupervised Learning Methods to Create Ontology Bases

Ontologies in current computer science parlance are computer based resources that represent agreed domain semantics. This paper first introduces ontologies in general and subsequently, in particular, shortly outlines the DOGMA ontology engineering approach that separates “atomic” conceptual relations from “predicative” domain rules. In the main part of the paper, we describe and experimentally evaluate work in progress on a potential method to automatically derive the atomic conceptual relations mentioned above from a corpus of English medical texts. Preliminary outcomes are presented based on the clustering of nouns and compound nouns according to co-occurrence frequencies in the subject-verb-object syntactic context.

Enhancing the business analysis function with semantics

This paper outlines a prototypical work bench which offers semantically enhanced analytical capabilities to the business analyst The business case for such an environment is outlined and user scenario development used to illustrate system requirements Based upon ideas from meta-discourse and exploiting advances within the fields of ontology engineering, annotation, natural language processing and personal knowledge management, the Analyst Work Bench offers the automated identification of, and between business discourse items with possible propositional content The semantically annotated results are visually presented allowing personalised report path traversal marked up against the original source.

Adapting the object role modelling method for ontology modelling

A recent evolution in the areas of artificial intelligence, database semantics and information systems is the advent of the Semantic Web that requires that software agents and web services exchange meaningful and unambiguous messages. A prerequisite for this kind of interoperability is the usage of an ontology. Currently, not many step-wise ontology engineering methodologies exist. This paper describes an outline of such a methodology based on ORM, a DB conceptual modelling method. The new methodology is to be situated in the ontology engineering framework of DOGMA, developed at VUB STAR Lab. One of the distinctive characteristics is that language related issues are taken into account from the on-set.