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dc.contributor.authorChen, Hsinchun
dc.contributor.authorChau, Michael
dc.contributor.authorZeng, Daniel
dc.date.accessioned2004-08-16T00:00:01Z
dc.date.available2010-06-18T23:45:07Z
dc.date.issued2002en_US
dc.date.submitted2004-08-16en_US
dc.identifier.citationCI Spider: a tool for competitive intelligence on the Web 2002, 34(1):1-17 Decision Support Systemsen_US
dc.identifier.urihttp://hdl.handle.net/10150/106357
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractCompetitive 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.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectInterneten_US
dc.subjectArtificial Intelligenceen_US
dc.subjectWorld Wide Weben_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial Intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherSpideren_US
dc.subject.otherCompetitive intelligenceen_US
dc.titleCI Spider: a tool for competitive intelligence on the Weben_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalDecision Support Systemsen_US
refterms.dateFOA2018-08-13T21:28:07Z
html.description.abstractCompetitive 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.


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