Name
Title | ||
|---|---|---|
Conceptual knowledge acquisition using automatically generated large-scale semantic networks |
Abstract | ||
|---|---|---|
We present a method for automatically creating large-scale semantic networks from natural language text, based on deep semantic analysis. We provide a robust and scalable implementation, and sketch various ways in which the representation may be deployed for conceptual knowledge acquisition. A translation to RDF establishes interoperability with a wide range of standardised tools, and bridges the gap to the field of semantic technologies. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-14197-3_23 | ICCS |
Keywords | Field | DocType |
sketch various way,deep semantic analysis,semantic technology,standardised tool,large-scale semantic network,natural language text,wide range,scalable implementation,conceptual knowledge acquisition,standardisation,semantic network,natural language,semantic technologies | Semantic technology,Semantic Web Stack,Information retrieval,Computer science,Semantic analytics,Semantic interoperability,Semantic grid,Semantic Web Rule Language,Semantic computing,Semantic data model | Conference |
Volume | ISSN | ISBN |
6208 | 0302-9743 | 3-642-14196-X |
Citations | PageRank | References |
2 | 0.52 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pia-Ramona Wojtinnek | 1 | 12 | 1.79 |
| Brian Harrington | 2 | 86 | 12.18 |
| Sebastian Rudolph | 3 | 966 | 59.18 |
| Stephen Pulman | 4 | 450 | 38.31 |