Comparing noun phrasing techniques for use with medical digital library tools
Journal of the American Society for Information Science - Special topic issue on digital libraries: part 2
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
An extensive empirical study of feature selection metrics for text classification
The Journal of Machine Learning Research
Applying Authorship Analysis to Extremist-Group Web Forum Messages
IEEE Intelligent Systems
Automatic Information Organization and Retrieval.
Automatic Information Organization and Retrieval.
Journal of the American Society for Information Science and Technology
Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums
ACM Transactions on Information Systems (TOIS)
CyberIR --- A Technological Approach to Fight Cybercrime
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Textual analysis of stock market prediction using breaking financial news: The AZFin text system
ACM Transactions on Information Systems (TOIS)
Text feature selection using ant colony optimization
Expert Systems with Applications: An International Journal
A survey of modern authorship attribution methods
Journal of the American Society for Information Science and Technology
Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
Management Science
Automatic online news monitoring and classification for syndromic surveillance
Decision Support Systems
Sentiment analysis of Chinese documents: From sentence to document level
Journal of the American Society for Information Science and Technology
Fighting cybercrime: a review and the Taiwan experience
Decision Support Systems - Special issue: Intelligence and security informatics
Fighting cybercrime: a KM perspective
PAISI'10 Proceedings of the 2010 Pacific Asia conference on Intelligence and Security Informatics
Spotlight: Cybercrime Knows No Borders
Infosecurity
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The problem of cybercrime is so serious and costs our society increasingly and significantly. Integrating the cybercrime materials of law enforcement is urgent need for fighting cybercrime internationally. This study proposes a feasible architecture of CybercrimeIR to collect and classify the useful cybercrime materials in investigator's perspective. In the experiments, this study firstly adopts text representation approaches and machine learning techniques (e.g. support vector machine, Naïve Bayesian, and C4.5) to classify useful cybercrime materials in investigators' perspective. The performance measure in accuracy can at least achieve to 90% while conducting feature selection with information gain. We believe the proposed architecture of CybercrimeIR is very useful for integrating cybercrime materials of law enforcement globally.