Interpreting the web-mining results by cognitive map and association rule approach

Authors:
Kun Chang Lee;Sangjae Lee
Affiliations:
Professor at SKK Business School, WCU Professor of Creativity Science at Department of Interaction Science, Sungkyunkwan University, Seoul 110-745, Republic of Korea;School of Business Administration, Sejong University, Seoul 143-747, Republic of Korea
Venue:
Information Processing and Management: an International Journal
Year:
2011

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Abstract

A variety of the web-mining techniques are now being extensively utilized to extract useful knowledge about customer behaviors on the Internet. However, the naive interpretation of the web-mining results would lead to poor decision on customer behaviors, which is likely to cause waste of time and efforts on managing electronic commerce strategy. To overcome this pitfall, this study proposes using the cognitive map-based interpretation of the web-mining results. Conventional approach to obtaining the web-mining results is based on the association rule approach (ARA), while the cognitive map approach (CMA) is believed to provide more robust support in interpreting the web-mining results. Therefore, to compare the interpretation capability of the two approaches, the four constructs such as perceived usefulness, causality, information richness, users' attitude and intention to use the approaches are adopted in the research model and tested against the questionnaire data. The test results obtained through applying the structural equation models reveal that CMA is comparable to ARA and the cognitive map has a great potential in helping enrich the interpretation of the web mining results and build more effective Internet business strategy.