Foundations of statistical natural language processing
Foundations of statistical natural language processing
Data mining: concepts and techniques
Data mining: concepts and techniques
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
A Linguistic Approach to Extracting Acronym Expansions from Text
Knowledge and Information Systems
Adapting a synonym database to specific domains
RANLPIR '00 Proceedings of the ACL-2000 workshop on Recent advances in natural language processing and information retrieval: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 11
Information extraction from syllabi for academic e-Advising
Expert Systems with Applications: An International Journal
Foundations and Trends in Databases
Clustering and classification of maintenance logs using text data mining
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
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A health care claims processing application is introduced which processes both structured and unstructured information associated with medical insurance claims. The application makes use of a natural language processing (NLP) engine, together with application-specific knowledge, written in a concept specification language. Using NLP techniques, the entities and relationships that act as indicators of recoverable claims are mined from management notes, call centre logs and patient records to identify medical claims that require further investigation. Text mining techniques can then be applied to find dependencies between different entities, and to combine indicators to provide scores to individual claims. Claims are scored to determine whether they involve potential fraud or abuse, or to determine whether claims should be paid by or in conjunction with other insurers or organizations. Dependencies between claims and other records can then be combined to create cases. Issues related to the design of the application are discussed, specifically the use of rule-based techniques which provide a capability for deeper analysis than traditionally found in statistical techniques.