Abstract
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Artificial Intelligence |
| Publisher | Springer |
| Publication date | 2005 |
| Publication status | Published - 2005 |
| Event | 15th International Symposium on Methodologies for Intelligent Systems, ISMIS 2005 - Saratoga Springs, United States Duration: 25 May 2005 → 28 May 2005 Conference number: 15 |
Conference
| Conference | 15th International Symposium on Methodologies for Intelligent Systems, ISMIS 2005 |
|---|---|
| Number | 15 |
| Country | United States |
| City | Saratoga Springs |
| Period | 25/05/2005 → 28/05/2005 |
Cite this
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On Automatic Modeling and Use of Domain-specific Ontologies. / Andreasen, Troels; Knappe, Rasmus; Bulskov, Henrik.
Lecture Notes in Artificial Intelligence. Springer, 2005.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research
TY - GEN
T1 - On Automatic Modeling and Use of Domain-specific Ontologies
AU - Andreasen, Troels
AU - Knappe, Rasmus
AU - Bulskov, Henrik
PY - 2005
Y1 - 2005
N2 - In this paper, we firstly introduce an approach to the modeling of a domain-specific ontology for use in connection with a given document collection. Secondly, we present a methodology for deriving conceptual similarity from the domain-specific ontology. Adopted for ontology representation is a specific lattice-based concept algebraic language by which ontologies are inherently generative. The modeling of a domain specific ontology is based on a general ontology built upon common knowledge resources as dictionaries and thesauri. Based on analysis of concept occurrences in the object document collection the general ontology is restricted to a domain specific ontology encompassing concepts instantiated in the collection. The resulting domain specific ontology and similarity can be applied for surveying the collection through key concepts and conceptual relations and provides a means for topic-based navigation. Finally, a measure of concept similarity is derived from the domain specific ontology based on occurrences, commonalities, and distances in the ontology.
AB - In this paper, we firstly introduce an approach to the modeling of a domain-specific ontology for use in connection with a given document collection. Secondly, we present a methodology for deriving conceptual similarity from the domain-specific ontology. Adopted for ontology representation is a specific lattice-based concept algebraic language by which ontologies are inherently generative. The modeling of a domain specific ontology is based on a general ontology built upon common knowledge resources as dictionaries and thesauri. Based on analysis of concept occurrences in the object document collection the general ontology is restricted to a domain specific ontology encompassing concepts instantiated in the collection. The resulting domain specific ontology and similarity can be applied for surveying the collection through key concepts and conceptual relations and provides a means for topic-based navigation. Finally, a measure of concept similarity is derived from the domain specific ontology based on occurrences, commonalities, and distances in the ontology.
M3 - Article in proceedings
BT - Lecture Notes in Artificial Intelligence
PB - Springer
ER -