Abstract
The workshop on Mining Online Health Reports (MOHRS) draws upon the rapidly developing field of Computational Health, focusing on textual content that has been gener- ated through various activities on the Web. Online user- generated information mining, especially from social media platforms and search engines, has been in the forefront of many research efforts, especially in the fields of Informa- tion Retrieval and Natural Language Processing. The in- corporation of such data and techniques in a number of health-oriented applications has provided strong evidence of the potential benefits, which include better population coverage, timeliness and applicability to places with less established health infrastructure. The workshop provides an opportunity to present relevant state-of-the-art research, and a venue for discussion between researchers with cross- disciplinary backgrounds. It will focus on the characterisa- tion of data sources, the essential methods for mining this textual information, as well as potential real-world applica- tions and the arising ethical issues. MOHRS '17 will feature 3 keynote talks and 4 accepted paper presentations, as well as a panel discussion.
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Collier, N., Limsopatham, N., Culotta, A., Conway, M., Cox, I. J., & Lampos, V. (2017). WSDM 2017 workshop on mining online health reports WSDM workshop summary. In WSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining (pp. 825–826). Association for Computing Machinery, Inc. https://doi.org/10.1145/3018661.3022761
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