Towards the Extraction of Intelligence about Competitor from the Web
In this paper we present a system framework for the extraction of intelligence about competitor from the Web. With the surprising increasing of the data volume in the Web, how to get useful intelligence about competitor has been an interesting issue. Previous study shows that most people prefer to look up information by competitor. We first analyze the requirements on the extraction of competitor intelligence from the Web and define three types of intelligence for competitor. And then a system framework to extract competitor intelligence from the Web is described. We discuss the three key issues of the system in detail, which are the profile intelligence extraction, the events intelligence extraction, and the relations intelligence extraction. Some new techniques to deal with those issues are introduced in the paper.
Keywordscompetitive intelligence competitor Web intelligence extraction
Unable to display preview. Download preview PDF.
- 1.LaMar, J.: Competitive Intelligence Survey Report (2007), http://joshlamar.com/documents/CITSurveyReport.pdf
- 3.Mikroyannidis, A., Theodoulidis, B., Persidis, A.: PARMENIDES: Towards Business Intelligence Discovery from Web Data. In: Proc. of IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006), pp. 1057–1060 (2006)Google Scholar
- 4.Kahaner, L.: Competitive Intelligence. Simon & Schuster, New York (1996)Google Scholar
- 5.Hotho, A., Nürnberger, A., Paass, G.: A Brief Survey of Text Mining. LDV Forum (LDVF) 20(1), 19–62 (2005)Google Scholar
- 8.Whitelaw, C., Kehlenbeck, A., Petrovic, N., et al.: Web-scale Named Entity Recognition. In: Proc. of CIKM 2008, pp. 123–132 (2008)Google Scholar
- 9.Sundheim, M.: Named Entity Task Definition-Version 2.1. In: Proc. of the Sixth Message Understanding Conference, pp. 319–332 (1995)Google Scholar
- 12.Sun, B., Mitra, P., Giles, C.L., et al.: Topic segmentation with shared topic detection and alignment of multiple documents. In: Proc. of SIGIR, pp. 199–206 (2007)Google Scholar
- 14.TIMEX2, http://timex2.mitre.org/
- 16.ACE (Automatic Content Extraction) English Annotation Guidelines for Relations, Version 6.2, Linguistic Data Consortium (2008), http://www.ldc.upenn.edu/Projects/ACE/