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
Semantic role labelling with tree conditional random fields
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Shallow information extraction from medical forum data
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Learning online discussion structures by conditional random fields
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Natural Language Processing (Almost) from Scratch
The Journal of Machine Learning Research
Social health data integration using semantic Web
Proceedings of the 27th Annual ACM Symposium on Applied Computing
An architecture for personalized health information retrieval
Proceedings of the 2012 international workshop on Smart health and wellbeing
Patient-Centered information extraction for effective search on healthcare forum
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Learning thread reply structure on patient forums
Proceedings of the 2013 international workshop on Data management & analytics for healthcare
PIKM 2013: the 6th ACM workshop for ph.d. students in information and knowledge management
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Online healthcare forums provide a valuable platform for people to share medical information and support each other. However, currently the rich information shared on healthcare forums has not been fully explored. In this work, we first motivate the need for patient-centric, multi-role, and multi-dimension information exploration. We then present our patient-centric information exploration prototype system and show its effectiveness with preliminary experiment evaluation. We have also identified some potential techniques for multi-role and multi-dimension information exploration.