TY - JOUR
T1 - CI Spider
T2 - A tool for competitive intelligence on the Web
AU - Chen, Hsinchun
AU - Chau, Michael
AU - Zeng, Daniel
N1 - Funding Information:
Hsinchun Chen is McClelland Professor of MIS and Andersen Professor of MIS at the University of Arizona, where he is the director of the Artificial Intelligence Lab and the director of the Hoffman E-Commerce Lab. His articles have appeared in Communications of the ACM, IEEE Computer, Journal of the American Society for Information Science and Technology, IEEE Expert, and many other publications. Professor Chen has received grant awards from NSF, DARPA, NASA, NIH, NIJ, NLM, NCSA, HP, SAP, 3COM, and AT&T. He serves on the editorial board of Decision Support Systems and the Journal of the American Society for Information Science and Technology and has served as the conference general chair in the International Conferences on Asian Digital Library in the past 4 years.
PY - 2002/12
Y1 - 2002/12
N2 - Competitive Intelligence (CI) aims to monitor a firm's external environment for information relevant to its decision-making process. As an excellent information source, the Internet provides significant opportunities for CI professionals as well as the problem of information overload. Internet search engines have been widely used to facilitate information search on the Internet. However, many problems hinder their effective use in CI research. In this paper, we introduce the Competitive Intelligence Spider, or CI Spider, designed to address some of the problems associated with using Internet search engines in the context of competitive intelligence. CI Spider performs real-time collection of Web pages from sites specified by the user and applies indexing and categorization analysis on the documents collected, thus providing the user with an up-to-date, comprehensive view of the Web sites of user interest. In this paper, we report on the design of the CI Spider system and on a user study of CI Spider, which compares CI Spider with two other alternative focused information gathering methods: Lycos search constrained by Internet domain, and manual within-site browsing and searching. Our study indicates that CI Spider has better precision and recall rate than Lycos. CI Spider also outperforms both Lycos and within-site browsing and searching with respect to ease of use. We conclude that there exists strong evidence in support of the potentially significant value of applying the CI Spider approach in CI applications.
AB - Competitive Intelligence (CI) aims to monitor a firm's external environment for information relevant to its decision-making process. As an excellent information source, the Internet provides significant opportunities for CI professionals as well as the problem of information overload. Internet search engines have been widely used to facilitate information search on the Internet. However, many problems hinder their effective use in CI research. In this paper, we introduce the Competitive Intelligence Spider, or CI Spider, designed to address some of the problems associated with using Internet search engines in the context of competitive intelligence. CI Spider performs real-time collection of Web pages from sites specified by the user and applies indexing and categorization analysis on the documents collected, thus providing the user with an up-to-date, comprehensive view of the Web sites of user interest. In this paper, we report on the design of the CI Spider system and on a user study of CI Spider, which compares CI Spider with two other alternative focused information gathering methods: Lycos search constrained by Internet domain, and manual within-site browsing and searching. Our study indicates that CI Spider has better precision and recall rate than Lycos. CI Spider also outperforms both Lycos and within-site browsing and searching with respect to ease of use. We conclude that there exists strong evidence in support of the potentially significant value of applying the CI Spider approach in CI applications.
KW - Competitive intelligence
KW - Document clustering
KW - Experimental research
KW - Internet searching and browsing
KW - Internet spider
KW - Noun phrasing
UR - http://www.scopus.com/inward/record.url?scp=0036885533&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0036885533&partnerID=8YFLogxK
U2 - 10.1016/S0167-9236(02)00002-7
DO - 10.1016/S0167-9236(02)00002-7
M3 - Article
AN - SCOPUS:0036885533
SN - 0167-9236
VL - 34
SP - 1
EP - 17
JO - Decision Support Systems
JF - Decision Support Systems
IS - 1
ER -