Hybrid System for Information Extraction from Social Media Text: Drug Abuse Case Study

Author:

Jenhani Ferdaous,Gouider Mohamed Salah,Said Lamjed Ben

Publisher

Elsevier BV

Subject

General Engineering

Reference35 articles.

1. Poibeau, et al. eds (2013). Multi-source, Multilingual Information Extraction and Summarization 11, Theory and Applications of Natural Language Processing, DOI 10.1007/978-3-642-28569-12, Springer-Verlag, Berlin Heidelberg. Chapter 2, J. Piskorski and R. Yangarber.

2. Delroy, Gary, Raminta, Amit, Drashti, Lu, Gaurish, Robert, Kera, Russel (2013). ‘PREDOSE: a semantic web platform for drug abuse epidemiology using social media’, Journal of biomedical informatics.

3. Liu, Chen (2013). Identifying Adverse Drug Events from Patient Social media: a case study for diabetes. University of Arizona.

4. Carbonell, Mayer, Bravo (2015). Exploring Brand-name drug mentions on Twitter for pharmacovigilance. Digital Healthcare Empowering Europeans. pp. 55-59.

5. Segua-bedmar, Martinez, Revert, Moreno-shneider (2015). Exploring Spanish health social media for detecting drug effects, Medical informatics and decision making, From Louhi 2014: The Fifth International Workshop on Health Text Mining and Information Analysis Gothenburg, Sweden.

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