Learning routing queries in a query zone
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Boosting and Rocchio applied to text filtering
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Active learning using adaptive resampling
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A study of thresholding strategies for text categorization
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Maximum likelihood estimation for filtering thresholds
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
A refinement approach to handling model misfit in text categorization
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Adaptive sampling for thresholding in document filtering and classification
Information Processing and Management: an International Journal
Focused crawling for both topical relevance and quality of medical information
Proceedings of the 14th ACM international conference on Information and knowledge management
Dynamic category profiling for text filtering and classification
Information Processing and Management: an International Journal
Interactive high-quality text classification
Information Processing and Management: an International Journal
Context-based online medical terminology navigation
Expert Systems with Applications: An International Journal
Identifying disease diagnosis factors by proximity-based mining of medical texts
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
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Healthcare information support (HIS) is essential in managing, gathering, and disseminating information for healthcare decision support through the Internet. To support HIS, text classification (TC) is a key kernel. Upon receiving a text of healthcare need (e.g. symptom description from patients) or healthcare information (e.g. information from medical literature and news), a text classifier may determine its corresponding categories (e.g. diseases), and hence subsequent HIS tasks (e.g. online healthcare consultancy and information recommendation) may be conducted. The key challenge lies on high-quality TC, which aims to classify most texts into suitable categories (i.e. recall is very high), while at the same time, avoid misclassifications of most texts (precision is very high). High-quality TC is particularly essential, since healthcare is a domain where an error may incur higher cost and/or serious problems. Unfortunately, high-quality TC was seldom achieved in previous studies. In the paper, we present a case study in which a high-quality classifier is built to support HIS in Chinese disease-related information, including the cause, symptom, curing, side-effect, and prevention of cancer. The results show that, without relying on domain knowledge and complicated processing, cancer information may be classified into suitable categories, with a controlled amount of confirmations.