PLOS launches Text Mining Collection
2013-04-18
PLOS has recently launched the Text Mining Collection, which is a compendium of major reviews and recent highlights published in the PLOS family of journals on the topic of text mining. The Collection acknowledges the growing body of work in the area of text mining research.
PLOS is one of the major publishers of Open Access scientific literature. The widespread application and societal benefits of text mining is most easily achieved under an Open Access model of publishing, where the barriers to obtaining published articles are minimized and the ability to remix and redistribute data extracted from text is explicitly permitted.
PLOS is one of the few Open Access publishers to provide an open Application Programming Interface to mine their journal content.
More information...
http://blogs.plos.org/everyone/2013/04/17/announcing-the-plos-text-mining-collection/
Previous item | Next item |
Back to news summary page |
Featured News
- Invited talk at the 8th Annual Women in Data Science Event at the American University of Beirut
- Invited talk at the 2nd Symposium on NLP for Social Good (NSG), University of Liverpool
- Postdoctoral research position in Athens, Greece. Application deadline: 18th March 2024
- Four-year funded PhD in collaboration with A*STAR, Singapore. Deadline 20 March 2024
- PhD opportunity in collaboration with Athens Univ. of Economics and Business. Deadline 31 Mar 2024
- iCASE EPSRC funded PhD- multimodal NLP - UoM & BAE - Application deadline 30th March 2024
- CFP: BIONLP 2024 and Shared Tasks @ ACL 2024
- Advances in Data Science and Artificial Intelligence Conference 2024
- New review article on emotion detection for misinformation
Other News & Events
- Invited talk at Annual Meeting of the Danish Society of Occupational and Environmental Medicine
- BioNLP 2024 accepted as workshop at ACL 2024
- Junichi Tsujii awarded Order of the Sacred Treasure, Gold Rays with Neck Ribbon
- Chinese Government AwardAward for PhD student Tianlin Zhang
- Keynote talk at EMBL-EBI industry club Machine Learning for Text Mining