Abstract
Automatic information extraction techniques such as named entity recognition and relation extraction have been developed but it is yet rare to apply them to various document types. In this paper, we applied them to academic literature and social media's contents in the field of diabetes to find distinctions between the perceptions of biomedical experts and the public. We analyzed and compared the experts' and the public's networks constituted by the extracted entities and relations. The results confirmed that there are some differences in their views, i.e., biomedical entities that interest them and relations within their knowledge range.
| Original language | English |
|---|---|
| Title of host publication | WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 57-58 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781450334730 |
| DOIs | |
| Publication status | Published - 2015 May 18 |
| Event | 24th International Conference on World Wide Web, WWW 2015 - Florence, Italy Duration: 2015 May 18 → 2015 May 22 |
Publication series
| Name | WWW 2015 Companion - Proceedings of the 24th International Conference on World Wide Web |
|---|
Other
| Other | 24th International Conference on World Wide Web, WWW 2015 |
|---|---|
| Country/Territory | Italy |
| City | Florence |
| Period | 15/5/18 → 15/5/22 |
Bibliographical note
Funding Information:This work was supported by the Bio-Synergy Research Project (NRF-2013M3A9C4078138) of the Ministry of Science, ICT and Future Planning through the National Research Foundation.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Software
