Name
Abstract | ||
|---|---|---|
This paper presents an automatic method for differentiating between instances and classes in a large scale taxonomy induced from the Wikipedia category network. The method exploits characteristics of the category names and the structure of the network. The approach we present is the first attempt to make this distinction automatically in a large scale resource. In contrast, this distinction has been made in WordNet and Cyc based on manual annotations. The result of the process is evaluated against ResearchCyc. On the subnetwork shared by our taxonomy and ResearchCyc we report 84.52% accuracy. |
Year | Venue | Keywords |
|---|---|---|
2008 | ESWC | large scale taxonomy,category name,large scale resource,automatic method,wikipedia category network,wikipedia taxonomy,manual annotation |
Field | DocType | Volume |
Noun phrase,Data mining,Information retrieval,Computer science,Computational linguistics,Exploit,WordNet,Subnetwork | Conference | 5021 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-68233-3 | 31 |
PageRank | References | Authors |
1.58 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cäcilia Zirn | 1 | 139 | 7.61 |
| Vivi Nastase | 2 | 523 | 41.30 |
| Michael Strube | 3 | 2142 | 137.32 |