Name
Abstract | ||
|---|---|---|
Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76298-0_61 | ISWC/ASWC |
Keywords | Field | DocType |
business intelligence,key piece,ontology-based information extraction,region information,practical e-business application,key enablers,statistical bi model,ontology-based extraction,semantic information,valuable information,information extraction,natural language | Ontology (information science),Ontology,Data mining,Information retrieval,Computer science,Semantic information,Information extraction,Business intelligence,Merge (version control),Database,Relationship extraction | Conference |
Volume | ISSN | ISBN |
4825 | 0302-9743 | 3-540-76297-3 |
Citations | PageRank | References |
51 | 2.27 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Horacio Saggion | 1 | 1119 | 112.62 |
| Adam Funk | 2 | 314 | 17.90 |
| Diana Maynard | 3 | 1799 | 160.95 |
| Kalina Bontcheva | 4 | 2538 | 211.33 |