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<Paper uid="W01-1005">
  <Title>Identification of relevant terms to support the construction of Domain Ontologies</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> In cooperating to work together (or even in interacting in social settings), people and organizations must communicate among themselves. However, due to different contexts and backgrounds, there can be different viewpoints, assumptions and needs regarding the same domain or the same problem. They may use different jargon and terminology, sometimes even confused, overlapping, and they may use concepts and evaluation methods that are mismatched or poorly defined.</Paragraph>
    <Paragraph position="1"> The consequence is the lack of a shared understanding that leads to a poor communication between people and organizations. In particular, when IT solutions are involved, this lack of a shared understanding impacts on:  systems components.</Paragraph>
    <Paragraph position="2"> The goals of an Ontology is to reduce (or eliminate) conceptual and terminological confusion. This is achieved by identifying and properly defining a set of relevant concepts that characterize a given application domain. With respect to a Thesaurus: An Ontology aims at describing concepts, whereas a Thesaurus aims at describing terms; An Ontology can be seen as an enriched Thesaurus where, besides the definitions and relationships among terms of a given domain, more conceptual knowledge, by means of richer semantic relationships, is represented. With respect to a Knowledge Base (KB): An Ontology can be seen as a KB whose goal is the description of the concepts necessary for talking about domains; A KB, in addition, includes the knowledge needed to model and elaborate a problem, derive new knowledge, prove theorems, or answer to intentional queries about a domain. Though the utility of domain Ontologies is now widely acknowledged in the IT community, several barriers must be overcome before Ontologies become practical and useful tools for shared knowledge management.</Paragraph>
    <Paragraph position="3"> We envisage three main areas where innovative computational solutions could significantly reduce the cost and effort of Ontology construction: * provide effective support for collaborative development of consensus Ontologies, since consensus is the first condition to be met in order to obtain the desired benefits from an Ontology * enable distributed development and access to Ontologies, since wide-spread usage of a resource outweighs the cost of development * develop tools to identify the relevant concepts and (semi-)automatically enrich with semantic information the nodes of the Ontology, thus reducing the cost and complexity of manually defining several thousand concepts In this paper, we describe SymOntos, an Ontology management system under development at our institution since the last several years. In designing SymOntos, we have been working to define innovative solutions concerning the three critical issues listed above. These solutions are currently being experimented in the context of the European project FETISH1, aimed at the definition of an interoperability platform for Small Medium Enterprises in the tourism sector.</Paragraph>
    <Paragraph position="4"> Though we will (very) briefly present SymOntos, this paper is concerned with the third issue, that is, the description of text mining methods and tools to automatically enrich the concept Ontology.</Paragraph>
    <Paragraph position="5"> In the FETISH Project, we decided to explore the possibility to support the extraction of initial shared/able knowledge from on-line textual documentation accessible from the Web.</Paragraph>
  </Section>
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