Managing Uncertainty in Expert Systems
Managing Uncertainty in Expert Systems
Mining Case Bases for Action Recommendation
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Mining Actionable Patterns by Role Models
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Developing event-condition-action rules in real-time active database
Proceedings of the 2007 ACM symposium on Applied computing
Action Rules and the GUHA Method: Preliminary Considerations and Results
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Mining action rules from scratch
Expert Systems with Applications: An International Journal
Advances in Music Information Retrieval
Advances in Music Information Retrieval
From Tinnitus Data to Action Rules and Tinnitus Treatment
GRC '10 Proceedings of the 2010 IEEE International Conference on Granular Computing
From data to classification rules and actions
International Journal of Intelligent Systems
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The extended tinnitus database consisting of 758 patients with information repeated from the original database of 555 patients, along with the addition of visits and a new questionnaire, the Tinnitus Function Index and Emotion Indexing Questionnaire, is used to mine for knowledge. New patients in the extended database represent those patients that have completed the Tinnitus Function Index questionnaire (TFI) [10]. The patient visits are separated and used for mining and action rule discovery based on all features and treatment success indicators including several new features tied to emotions (based on a mapping from TFI to Emotion Indexing Questionnaire (EIQ) [14]; EIQ questionnaire is used by our team to build personalized classifiers for automatic indexing of music by emotions). We propose a link between TFI and EIQ leading to a creation of new features in the extended tinnitus database. Then, we extract knowledge from this new database in the form of association action rules to assist with understanding and validation of diagnosis and treatment outcomes.