In this paper, we explore a new data mining capability which involves mining Web transaction patterns for an electronic commerce (EC) environment. We propose an innovative mining model that takes both the traveling patterns and purchasing patterns of customers into consideration. First, we develop algorithm WR to extract meaningful Web transaction records from Web transactions so as to filter out the effect of irrelevant traversal sequences. Second, we devise algorithm WTM for determining the large transaction patterns from the Web transaction records obtained.
CITATION STYLE
Yun, C. H., & Chen, M. S. (2000). Mining web transaction patterns in an electronic commerce environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1805, pp. 216–219). Springer Verlag. https://doi.org/10.1007/3-540-45571-x_28
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