Mining E-Commerce Data to Analyze the Target Customer Behavior

@inproceedings{citeulike:2951474, abstract = {In the advent of the information era, e-commerce has developed rapidly and has become significant for every business. With the advanced information technologies, firms are now able to collect and store mountains of data describing their myriad offerings and diverse customer profiles, from which they seek to derive information about their customers' needs and wants. Traditional forecasting methods are no longer suitable for these business situations. This research used the principles of data mining to cluster customer segments by using k-means algorithm and data from Web log of various e-commerce Websites. Consequently, the results showed that there was a clear distinction between the segments in terms of customer behavior.}, author = {Jiang, Yuantao and Yu, Siqin }, booktitle = {Knowledge Discovery and Data Mining, 2008. WKDD 2008. International Workshop on}, citeulike-article-id = {2951474}, doi = {10.1109/WKDD.2008.90}, journal = {Knowledge Discovery and Data Mining, 2008. WKDD 2008. International Workshop on}, keywords = {e-commerce}, pages = {406--409}, posted-at = {2008-07-02 09:06:29}, priority = {2}, title = {Mining E-Commerce Data to Analyze the Target Customer Behavior}, url = {http://dx.doi.org/10.1109/WKDD.2008.90}, year = {2008} }

TY - CONF ID - citeulike:2951474 L3 - citeulike-article-id:2951474 TI - Mining E-Commerce Data to Analyze the Target Customer Behavior T2 - Knowledge Discovery and Data Mining, 2008. WKDD 2008. International Workshop on JF - Knowledge Discovery and Data Mining, 2008. WKDD 2008. International Workshop on SP - 406 EP - 409 N2 - In the advent of the information era, e-commerce has developed rapidly and has become significant for every business. With the advanced information technologies, firms are now able to collect and store mountains of data describing their myriad offerings and diverse customer profiles, from which they seek to derive information about their customers' needs and wants. Traditional forecasting methods are no longer suitable for these business situations. This research used the principles of data mining to cluster customer segments by using k-means algorithm and data from Web log of various e-commerce Websites. Consequently, the results showed that there was a clear distinction between the segments in terms of customer behavior. KW - e-commerce AU - Jiang, Yuantao AU - Yu, Siqin PY - 2008/// UR - http://dx.doi.org/10.1109/WKDD.2008.90 ER -