Name
Abstract | ||
|---|---|---|
In the presence of an ever growing amount of information, organizations and human users need to be able to focus on certain key pieces of information and to intentionally ignore all other possibly relevant parts. Knowledge about complex systems that is represented in ontologies yields collections of axioms that are too large for human users to browse, let alone to comprehend or reason about it. We introduce the notion of an ontology excerpt as being a fixed-size subset of an ontology, consisting of the most relevant axioms for a given set of terms. These axioms preserve as much as possible the knowledge about the considered terms described in the ontology. We consider different extraction techniques for ontology excerpts based on methods from the area of information retrieval. To evaluate these techniques, we propose to measure the degree of incompleteness of the resulting excerpts using the notion of logical difference. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-25159-2_7 | KSEM |
Field | DocType | Volume |
Ontology (information science),Complex system,Data mining,Ontology-based data integration,Ontology,Process ontology,Information retrieval,Axiom,Computer science,Suggested Upper Merged Ontology,Upper ontology | Conference | 9403 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.35 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jieying Chen | 1 | 11 | 6.43 |
| Michel Ludwig | 2 | 3 | 4.12 |
| Yue Ma | 3 | 6 | 8.90 |
| Dirk Walther | 4 | 10 | 3.72 |