Characterizing browsing strategies in the World-Wide Web
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
Frontiers of electronic commerce
Frontiers of electronic commerce
Scalable parallel data mining for association rules
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Integrating association rule mining with relational database systems: alternatives and implications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Marketing on the internet - who can benefit from an online marketing approach
Decision Support Systems
Adaptive Retrieval Agents: Internalizing Local Contextand Scaling up to the Web
Machine Learning - Special issue on information retrieval
Data mining: concepts and techniques
Data mining: concepts and techniques
Create customer-effective e-services
E-business Advisor
Knowledge management and data mining for marketing
Decision Support Systems - Knowledge management support of decision making
Dynamic rule refinement in knowledge-based data mining systems
Decision Support Systems - Special issue on decision support in the new millennium
A literature review and classification of electronic commerce research
Information and Management
Capitalizing on Knowledge: From E-Commerce to K-Commerce
Capitalizing on Knowledge: From E-Commerce to K-Commerce
Data Warehousing in the Real World: A Practical Guide for Building Decision Support Systems
Data Warehousing in the Real World: A Practical Guide for Building Decision Support Systems
Management Information Systems
Management Information Systems
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
A Cube Model and Cluster Analysis for Web Access Sessions
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior
Information Systems Research
Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics
Information Systems Research
Complementing search engines with online web mining agents
Decision Support Systems - Special issue: Web data mining
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Denotation and connotation in the human-computer interface: the 'Save as...' command
Behaviour & Information Technology
Long-term working memory and interrupting messages in human-computer interaction
Behaviour & Information Technology
Internet Marketing: Building Advantage in a Networked Economy
Internet Marketing: Building Advantage in a Networked Economy
Experiments on query expansion for internet yellow page services using web log mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Context-based market basket analysis in a multiple-store environment
Decision Support Systems
Expert Systems with Applications: An International Journal
Integrating web mining and neural network for personalized e-commerce automatic service
Expert Systems with Applications: An International Journal
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In the digital market, attracting sufficient online traffic in a business to customer Web site is vital to an online business's success. The changing patterns of Internet surfer access to e-commerce sites pose challenges for the Internet marketing teams of online companies. For e-business to grow, a system must be devised to provide customers' preferred traversal patterns from product awareness and exploration to purchase commitment. Such knowledge can be discovered by synthesizing a large volume of Web access data through information compression to produce a view of the frequent access patterns of e-customers. This paper develops constructs for measuring the online movement of e-customers, and uses a mental cognitive model to identify the four important dimensions of e-customer behavior, abstract their behavioral changes by developing a three-phase e-customer behavioral graph, and tests the instrument via a prototype that uses an online analytical mining (OLAM) methodology. The knowledge discovered is expected to foster the development of a marketing plan for B2C Web sites. A prototype with an empirical Web server log file is used to verify the feasibility of the methodology.