Information Retrieval
Visual Web Information Extraction with Lixto
Proceedings of the 27th International Conference on Very Large Data Bases
The Lixto data extraction project: back and forth between theory and practice
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Multi-paradigm Java-Prolog integration in tuProlog
Science of Computer Programming
Online supervised spam filter evaluation
ACM Transactions on Information Systems (TOIS)
Guest editorial: special issue on Inductive Logic Programming
Machine Learning
Evaluation of spam detection and prevention frameworks for email and image spam: a state of art
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Parallel ILP for distributed-memory architectures
Machine Learning
Dynamically weighted hidden Markov model for spam deobfuscation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Rule-based Sam e-mail annotation
RR'10 Proceedings of the Fourth international conference on Web reasoning and rule systems
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A new system for spam e-mail annotation by end-users is presented. It is based on the recursive application of handwritten annotation rules by means of an inferential engine based on Logic Programming. Annotation rules allow the user to express nuanced considerations that depend on deobfuscation, word (non-)occurrence and structure of the message in a straightforward, human-readable syntax. We show that a sample collection of annotation rules are effective on a relevant corpus that we have assembled by collecting emails that have escaped detection by the industry-standard SpamAssassin filter. The system presented here is intended as a personal tool enforcing personalized annotation rules that would not be suitable for the general e-mail traffic.