A Taxonomy Learning Method and Its Application to Characterize a Scientific Web Community
| Autor: | Alessandro Cucchiarelli, Michaël Petit, Paola Velardi |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Competitive intelligence
business.industry Computer science Interoperability Ontology (information science) Enterprise interoperability Knowledge acquisition Computer Science Applications Semantic heterogeneity World Wide Web Text mining Computational Theory and Mathematics Taxonomy (general) Business intelligence Ontology Information system The Internet business Information Systems Web community |
| Zdroj: | IEEE Transactions on Knowledge and Data Engineering. 19:180-191 |
| ISSN: | 1041-4347 |
| DOI: | 10.1109/tkde.2007.21 |
| Popis: | The need to extract and manage domain-specific taxonomies has become increasingly relevant in recent years. A taxonomy is a form of business intelligence used to integrate information, reduce semantic heterogeneity, describe emergent communities and interest groups, and facilitate communication between information systems. We present a semiautomated strategy to extract domain-specific taxonomies from Web documents and its application to model a network of excellence in the emerging research field of enterprise interoperability |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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