From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Principles of data mining
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
The Journal of Machine Learning Research
Dependency Tree Kernels for Relation Extraction from Natural Language Text
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Named Entity Recognition of Spoken Documents Using Subword Units
ICSC '09 Proceedings of the 2009 IEEE International Conference on Semantic Computing
Hadoop: The Definitive Guide
New filtering approaches for phishing email
Journal of Computer Security - EU-Funded ICT Research on Trust and Security
Online phishing classification using adversarial data mining and signaling games
ACM SIGKDD Explorations Newsletter
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During the last decades, the disciplines of Data Mining and Operations Research have been working mostly independent of each other. However, the increasing complexity of today's applications in areas such as business, medicine, and science requires more and more interaction between both disciplines. On the one hand, several data mining algorithms are based on optimization methods. On the other hand, in several applications the pure Knowledge Discovery in Databases KDD process is not sufficient since it does not take explicitly into account the entire decision process. This report presents future trends in Business Analytics and Optimization discussed at the panel sessions during the workshop on Business Analytics and Optimization BAO'2010.