2008
Infrastructure for Dynamic Knowledge Integration -- Automated Biomedical Ontology Extension Using Textual Resources
NOVÁČEK, Vít, Loredana LAERA, Siegfried HANDSCHUH a Brian DAVISZákladní údaje
Originální název
Infrastructure for Dynamic Knowledge Integration -- Automated Biomedical Ontology Extension Using Textual Resources
Název česky
Infrastructure for Dynamic Knowledge Integration -- Automated Biomedical Ontology Extension Using Textual Resources
Autoři
NOVÁČEK, Vít (203 Česká republika, garant), Loredana LAERA (380 Itálie), Siegfried HANDSCHUH (276 Německo) a Brian DAVIS (372 Irsko)
Vydání
Journal of Biomedical Informatics, Amsterdam, Elsevier, 2008, 1532-0464
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Irsko
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 1.924
Kód RIV
RIV/00216224:14330/08:00024234
Organizační jednotka
Fakulta informatiky
UT WoS
000260137300013
Klíčová slova anglicky
dynamic ontology integration; ontology evolution; ontology alignment and negotiation; ontology learning; biomedical ontologies; knowledge acquisition; lifecycle
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 3. 11. 2008 12:36, doc. Mgr. Bc. Vít Nováček, PhD
V originále
We present a novel ontology integration technique that explicitly takes the dynam- ics and data-intensiveness of e-health and biomedicine application domains into ac- count. Changing and growing knowledge, possibly contained in unstructured natural language resources, is handled by application of cutting-edge Semantic Web tech- nologies. In particular, semi-automatic integration of ontology learning results into a manually developed ontology is employed. This integration bases on automatic negotiation of agreed alignments, inconsistency resolution and natural language generation methods. Their novel combination alleviates the end-user effort in the incorporation of new knowledge to large extent. This allows for efficient application in many practical use cases, as we show in the paper.
Česky
We present a novel ontology integration technique that explicitly takes the dynam- ics and data-intensiveness of e-health and biomedicine application domains into ac- count. Changing and growing knowledge, possibly contained in unstructured natural language resources, is handled by application of cutting-edge Semantic Web tech- nologies. In particular, semi-automatic integration of ontology learning results into a manually developed ontology is employed. This integration bases on automatic negotiation of agreed alignments, inconsistency resolution and natural language generation methods. Their novel combination alleviates the end-user effort in the incorporation of new knowledge to large extent. This allows for efficient application in many practical use cases, as we show in the paper.
Návaznosti
| 1ET100300419, projekt VaV |
|