Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Automatic personalization based on Web usage mining
Communications of the ACM
ACM SIGKDD Explorations Newsletter
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Web Usage Mining as a Tool for Personalization: A Survey
User Modeling and User-Adapted Interaction
Introduction To Business Data Mining
Introduction To Business Data Mining
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Dynamic personalization of web sites without user intervention
Communications of the ACM - Spam and the ongoing battle for the inbox
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data
Interpreting the web-mining results by cognitive map and association rule approach
Information Processing and Management: an International Journal
Personalizing group recommendation to social network users
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part I
Using lexicometry and vocabulary analysis techniques to detect a signature for web profile
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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The purpose of this study is to identify potential customers of online bookstores through web content mining without customers' transaction records and demographic information. Our study first creates a list of scholars whose research field is in information technology and categories of IT expertise. We then use a search engine to count the numbers of web pages related to scholars and expertise. These data are pre-processed with three key steps before being used: filtering abnormal data, normalizing data, and generating binary data. Association analysis and hierarchical cluster analysis are employed to generate the clusters of scholars and the clusters of expertise. In order to test the accuracy of using web mining to predict clients' interested booklists, our study evaluates the accuracy of prediction through survey. The results show that the accuracy rate of the recommended booklists targeted on potential customers (scholars) is statistically significant.