Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
ACM SIGKDD Explorations Newsletter
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature Engineering for Text Classification
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Using data mining as a strategy for assessing asynchronous discussion forums
Computers & Education
Text classification in Asian languages without word segmentation
AsianIR '03 Proceedings of the sixth international workshop on Information retrieval with Asian languages - Volume 11
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
When to jump in: The role of the instructor in online discussion forums
Computers & Education
The class imbalance problem: A systematic study
Intelligent Data Analysis
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Boosting for text classification with semantic features
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Expert Systems with Applications: An International Journal
Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Monitoring student progress using virtual appliances: A case study
Computers & Education
Improving user experience with case-based reasoning systems using text mining and Web 2.0
Expert Systems with Applications: An International Journal
Computers in Human Behavior
An overview of web mining in education
Proceedings of the 17th Panhellenic Conference on Informatics
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As course management systems (CMS) gain popularity in facilitating teaching. A forum is a key component to facilitate the interactions among students and teachers. Content analysis is the most popular way to study a discussion forum. But content analysis is a human labor intensity process; for example, the coding process relies heavily on manual interpretation; and it is time and energy consuming. In an asynchronous virtual learning environment, an instructor needs to keep monitoring the discussion forum from time to time in order to maintain the quality of a discussion forum. However, it is time consuming and difficult for instructors to fulfill this need especially for K12 teachers. This research proposes a genre classification system, called GCS, to facilitate the automatic coding process. We treat the coding process as a document classification task via modern data mining techniques. The genre of a posting can be perceived as an announcement, a question, clarification, interpretation, conflict, assertion, etc. This research examines the coding coherence between GCS and experts' judgment in terms of recall and precision, and discusses how we adjust the parameters of the GCS to improve the coherence. Based on the empirical results, GCS adopts the cascade classification model to achieve the automatic coding process. The empirical evaluation of the classified genres from a repository of postings in an online course on earth science in a senior high school shows that GCS can effectively facilitate the coding process, and the proposed cascade model can deal with the imbalanced distribution nature of discussion postings. These results imply that GCS based on the cascade model can perform as an automatic posting coding system.