Temporal Company Relation Mining from the Web
Relationships between companies and business events of company relation changing can act as the most important factors to conduct market analysis and business management. However, it is very difficult to track company relations and to detect the related events, because the relations change rapidly and continuously. Existing technologies are limited to analysis of non-temporal relations or temporal tracking web data in a single feature. Our work targets temporal and multiple-type relation mining. The proposed method automates relation instance extraction from the Web, temporal relation graph creation, and business event detection based on the created temporal graph. In the experiment, more than 70 thousand relation instances were extracted from 1.7 million English news articles, and a temporal relation graph of 255 companies from 1995 to 2007 was generated, and acquisition events and cases of competition relation evolution were detected. These results show our method is effective.
KeywordsBusiness Activity Analysis Knowledge Acquisition Graph Theory
Unable to display preview. Download preview PDF.
- 2.Appelt, D.: An introduction to information extraction. Artificial Intelligence Communications 12(3), 161–172 (1999)Google Scholar
- 5.Cunningham, H.: Information Extraction, Automatic. Encyclopedia of Language and Linguistics (2005)Google Scholar
- 6.Grey, W., Olavson, T., et al.: The role of e-marketplaces in relationship-based supply chains: A survey. IBM Systems Journal 44(1) (2005)Google Scholar
- 7.Hou, X., Liu, T., et al.: Connection Network Intelligence (2006), http://www.research.ibm.com/-jam/CNI_Jam_Demo_PPT_v1.5.pdf.2006
- 11.Hu, M., Liu, B.: Mining and summarizing customer reviews. ACM SIGKDD, 168–177 (2004)Google Scholar
- 12.Liu, B., Zhao, K., et al.: Visualizing Web Site Comparisons. In: WWW 2002 (2002)Google Scholar
- 13.Liu, J., Wagner, E., et al.: Compare&Contrast: Using the Web to Discover Comparable Cases for News Stories. In: WWW 2007, pp. 541–550 (2007)Google Scholar
- 14.McCoy, D.W.: Business Activity Monitoring: Calm Before the Storm. Gartner Research, ID: LE-15-9727 (2002)Google Scholar
- 15.Morinaga, S., Yamanishi, K., et al.: Mining Product Reputations on the Web. In: KDD 2002, pp. 341–349 (2002)Google Scholar
- 16.Page, L., Brin, S.: The PageRank Citation Ranking: Bringing Order to the Web. Stanford Technical Report (1998)Google Scholar
- 18.Scott, J.: Social Network Analysis. Sage, Thousand Oaks (1992)Google Scholar
- 19.Tateishi, K., Ishiguro, Y., et al.: A Reputation Search Engine that Collects People’s Opinions by Information Extraction Technology. IPSJ Transactions on Databases 22, 115–123 (2004)Google Scholar