Name
Abstract | ||
|---|---|---|
This paper focuses on how to construct domain ontologies, in particular, a hierarchically structured set of domain concepts
without concept definitions, reusing a machine readable dictionary (MRD) and making it adjusted to specific domains. In doing
so, we must deal with concept drift, which means that the senses of concepts change depending on application domains. So here
are presented the following two strategies: match result analysis and trimmed result analysis. The strategies try to identify
which part may stay or should be moved, analyzing spell match results between given input domain terms and a MRD. We have
done case studies in the filed of some law. The empirical results show us that our system can support a user in constructing
a domain ontology.
|
Year | DOI | Venue |
|---|---|---|
1998 | 10.1007/BFb0095269 | PRICAI |
Keywords | Field | DocType |
domain ontology rapid development,development environment,concept drift | Information system,Ontology,Data mining,Computer science,Artificial intelligence,Spell,Systems architecture,Ontology (information science),Knowledge representation and reasoning,Information retrieval,Concept drift,Machine-readable dictionary,Machine learning | Conference |
Volume | ISSN | ISBN |
1531 | 0302-9743 | 3-540-65271-X |
Citations | PageRank | References |
10 | 0.85 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rieko Sekiuchi | 1 | 10 | 0.85 |
| Chizuru Aoki | 2 | 10 | 0.85 |
| Masaki Kurematsu | 3 | 21 | 3.17 |
| Takahira Yamaguchi | 4 | 270 | 30.67 |