Abstract
Identifying competitors for an individual company or a group of companies is important for businesses. Although people can consult paid company profile resources such as Hoover’s and Mergent, these sources are incomplete in company relationship coverage. We present an approach that uses graph-theoretic measures and machine learning techniques to achieve automated discovery of competitor relationships on the basis of structure of an intercompany network derived from company citations (cooccurrence) in online news articles. We also estimate to what extent our approach could extend the competitor relationships available from the data sources, Hoover’s and Mergent.
| Original language | English (US) |
|---|---|
| State | Published - 2009 |
| Externally published | Yes |
| Event | 30th International Conference on Information Systems, ICIS 2009 - Phoenix, AZ, United States Duration: Dec 15 2009 → Dec 18 2009 |
Other
| Other | 30th International Conference on Information Systems, ICIS 2009 |
|---|---|
| Country/Territory | United States |
| City | Phoenix, AZ |
| Period | 12/15/09 → 12/18/09 |
Keywords
- Business news
- Classification in networked data
- Competitor discovery
- Web mining
ASJC Scopus subject areas
- Information Systems