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  • × theme_ss:"Begriffstheorie"
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Hovy, E.: Comparing sets of semantic relations in ontologies (2002) 0.00 
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    Abstract
    A set of semantic relations is created every time a domain modeler wants to solve some complex problem computationally. These relations are usually organized into ontologies. But three is little standardization of ontologies today, and almost no discussion an ways of comparing relations, of determining a general approach to creating relations, or of modeling in general. This chapter outlines an approach to establishing a general methodology for comparing and justifying sets of relations (and ontologies in general). It first provides several dozen characteristics of ontologies, organized into three taxonomies of increasingly detailed features, by which many essential characteristics of ontologies can be described. These features enable one to compare ontologies at a general level, without studying every concept they contain. But sometimes it is necessary to make detailed comparisons of content. The chapter then illustrates one method for determining salient points for comparison, using algorithms that semi-automatically identify similarities and differences between ontologies.
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    a
  2. Hetzler, B.: Visual analysis and exploration of relationships (2002) 0.00 
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    Abstract
    Relationships can provide a rich and powerful set of information and can be used to accomplish application goals, such as information retrieval and natural language processing. A growing trend in the information science community is the use of information visualization-taking advantage of people's natural visual capabilities to perceive and understand complex information. This chapter explores how visualization and visual exploration can help users gain insight from known relationships and discover evidence of new relationships not previously anticipated.
    Type
    a
  3. Evens, M.: Thesaural relations in information retrieval (2002) 0.00 
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    Abstract
    Thesaural relations have long been used in information retrieval to enrich queries; they have sometimes been used to cluster documents as well. Sometimes the first query to an information retrieval system yields no results at all, or, what can be even more disconcerting, many thousands of hits. One solution is to rephrase the query, improving the choice of query terms by using related terms of different types. A collection of related terms is often called a thesaurus. This chapter describes the lexical-semantic relations that have been used in building thesauri and summarizes some of the effects of using these relational thesauri in information retrieval experiments
    Type
    a

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