Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A vector space model for automatic indexing
Communications of the ACM
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Teaching an introductory course in data mining
ITiCSE '05 Proceedings of the 10th annual SIGCSE conference on Innovation and technology in computer science education
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
A data mining course for computer science: primary sources and implementations
Proceedings of the 37th SIGCSE technical symposium on Computer science education
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Exposure to research through replication of research: a case in complex networks
ITiCSE '09 Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education
Improving an undergraduate data mining course with real-world projects
Journal of Computing Sciences in Colleges
Emphasizing ethics and privacy preservation in an undergraduate data mining course
Journal of Computing Sciences in Colleges
Course-embedded research in software development courses
Proceedings of the 45th ACM technical symposium on Computer science education
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The new interdisciplinary field of Data Mining emerged in the early 1990s as a response to the profusion of digital data generated in numerous fields such as biology, chemistry, astronomy, advertising, banking and finance, retail market, stock market, and the WWW. In this paper, I describe an undergraduate course in Data Mining offered at the College of Saint Benedict and Saint John's University in Spring of 2007 as a CSCI-317-upper-division "Topics in Computer Science"- course, entitled "Data Intelligence." One of the main objectives of the course was to engage students in experimental computing research through a number of carefully planned research activities resulting in better understanding of the course contents and deeper insights into the challenges faced by the data mining community.