eprintid: 1550379
rev_number: 32
eprint_status: archive
userid: 608
dir: disk0/01/55/03/79
datestamp: 2017-04-15 21:21:21
lastmod: 2021-11-15 01:52:43
status_changed: 2017-08-02 11:01:10
type: proceedings_section
metadata_visibility: show
creators_name: Collier, N
creators_name: Limsopatham, N
creators_name: Culotta, A
creators_name: Conway, M
creators_name: Cox, IJ
creators_name: Lampos, V
title: WSDM 2017 workshop on mining online health reports WSDM workshop summary
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Natural Language Processing; Machine Learning; Compu-
tational Health; User-Generated Content
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
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 generated through the various facets of Web activity. 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 Information Retrieval and Natural Language Processing. The incorporation of such data and techniques in a number of health-oriented applications has provided strong evidence about the potential benefits, which include better population coverage, timeliness and the operational ability in places with less established health infrastructure. The workshop aims to create a platform where relevant state-of-the-art research is presented, but at the same time discussions among researchers with cross-disciplinary backgrounds can take place. It will focus on the characterisation of data sources, the essential methods for mining this textual information, as well as potential real-world applications and the arising ethical issues. MOHRS '17 will feature 3 keynote talks and 4 accepted paper presentations, together with a panel discussion session.
date: 2017-02-02
date_type: published
publisher: ACM
official_url: http://dx.doi.org/10.1145/3018661.3022761
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1285840
doi: 10.1145/3018661.3022761
isbn_13: 9781450346757
lyricists_name: Cox, Ingemar
lyricists_name: Lampos, Vasileios
lyricists_id: IJCOX77
lyricists_id: VLAMP72
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
series: ACM International Conference on Web Search and Data Mining
publication: WSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining
volume: 10
place_of_pub: New York, USA
pagerange: 825-826
event_title: WSDM '17, Tenth ACM International Conference on Web Search and Data Mining, 6-10 February 2017, Cambridge, UK
book_title: WSDM '17: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining
editors_name: de Rijke, M
editors_name: Shokouhi, M
editors_name: Tomkins, A
editors_name: Zhang, M
citation:        Collier, N;    Limsopatham, N;    Culotta, A;    Conway, M;    Cox, IJ;    Lampos, V;      (2017)    WSDM 2017 workshop on mining online health reports WSDM workshop summary.                     In: de Rijke, M and Shokouhi, M and Tomkins, A and Zhang, M, (eds.) WSDM '17: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining.  (pp. pp. 825-826).  ACM: New York, USA.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1550379/1/Collier_WSDM_2017_workshop.pdf