Automatic Knowledge Acquisition and Integration Technique: Application to Large Scale Taxonomy Extraction and Document Annotation

NOVÁČEK, Vít. Automatic Knowledge Acquisition and Integration Technique: Application to Large Scale Taxonomy Extraction and Document Annotation. In Enterprise Information Systems (ICEIS 2007, revised selected papers). Berlin/Heidelberg: Springer-Verlag, 2008, s. 160-172. IX. ISSN 1865-1348.

Základní údaje

• Originální název: Automatic Knowledge Acquisition and Integration Technique: Application to Large Scale Taxonomy Extraction and Document Annotation
• Název česky: Automatic Knowledge Acquisition and Integration Technique: Application to Large Scale Taxonomy Extraction and Document Annotation
• Autoři: NOVÁČEK, Vít (203 Česká republika, garant, domácí).
• Vydání: Berlin/Heidelberg, Enterprise Information Systems (ICEIS 2007, revised selected papers), od s. 160-172, 13 s. IX, 2008.
• Nakladatel: Springer-Verlag

Další údaje

• Originální jazyk: angličtina
• Typ výsledku: Kapitola resp. kapitoly v odborné knize
• Obor: 10201 Computer sciences, information science, bioinformatics
• Stát vydavatele: Irsko
• Utajení: není předmětem státního či obchodního tajemství
• WWW: SpringerLink
• Kód RIV: RIV/00216224:14330/08:00040380
• Organizační jednotka: Fakulta informatiky
• ISSN: 1865-1348
• UT WoS: 000261372700013
• Klíčová slova anglicky: ontology engineering; ontology learning; ontology integration; taxonomy acquisiton; uncertainty; knowledge representation
• Štítky: knowledge representation, ontology engineering, ontology integration, ontology learning, taxonomy acquisiton, uncertainty
• Příznaky: Mezinárodní význam, Recenzováno

Anotace

We present new results of our research on integration of on- tologies created automatically by means of Human Language Technolo- gies. The research is related to OLE (Ontology LEarning)1 - a project aimed at bottom-up generation and merging of ontologies. It utilises a proposal of expressive uncertain knowledge representation framework called ANUIC (Adaptive Net of Universally Interrelated Concepts). We discuss our recent achievements in taxonomy acquisition and show how even simple application of the principles of ANUIC can improve the results of initial knowledge extraction methods. We also suggest an algorithm for large-scale automatic annotation of natural language documents, applying uncertain knowledge bases created using our approach.

Anotace česky

We present new results of our research on integration of on- tologies created automatically by means of Human Language Technolo- gies. The research is related to OLE (Ontology LEarning)1 - a project aimed at bottom-up generation and merging of ontologies. It utilises a proposal of expressive uncertain knowledge representation framework called ANUIC (Adaptive Net of Universally Interrelated Concepts). We discuss our recent achievements in taxonomy acquisition and show how even simple application of the principles of ANUIC can improve the results of initial knowledge extraction methods. We also suggest an algorithm for large-scale automatic annotation of natural language documents, applying uncertain knowledge bases created using our approach.

Návaznosti

• 1ET100300419, projekt VaV: Název: Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu

Investor: Akademie věd ČR, Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu