Integrating ontological and linguistic knowledge for conceptual information extraction
| Autor: | Michele Vindigni, Fabio Massimo Zanzotto, Roberto Basili |
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| Rok vydání: | 2004 |
| Předmět: |
Vocabulary
Computer science media_common.quotation_subject WordNet Inference Reuse computer.software_genre Domain (software engineering) Body of knowledge Databases Knowledge-based systems Text mining Ontologies Domain analysis Investments Data mining Taxonomy media_common Settore INF/01 - Informatica business.industry Costs Intelligent structures Text categorization Linguistics Information extraction Ontology Domain engineering Domain knowledge Artificial intelligence Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni business computer Natural language processing |
| Zdroj: | Web Intelligence |
| DOI: | 10.1109/wi.2003.1241190 |
| Popis: | Text understanding makes strong assumptions about the conceptualisation of the underlying knowledge domain. This mediates between the accomplishment of the specific task at the one hand and the knowledge expressed in the target text fragments at the other. However, building domain conceptualisations from scratch is a very complex and time-consuming task. Traditionally, the reuse of available domain resources, although not constituting always the best, has been applied as an accurate and cost effective solution. Here, we investigate the possibility of exploiting sources of domain knowledge (e.g. a subject reference system) to build a linguistically motivated domain concept hierarchy. The limitation connected with the use of domain taxonomies as ontological resources will be firstly discussed in the specific light of IE, i.e. for supporting linguistic inference. We then define a method for integrating the taxonomical domain knowledge and a general-purpose lexical knowledge base, like WordNet. A case study, i.e. the integration of the MeSH, Medical Subject Headings, and WordNet, will be then presented as a proof of the effectiveness and accuracy of the overall approach. |
| Databáze: | OpenAIRE |
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