Session 6 - Machine learning and NLP for EM
Date: Friday, October 4rth, 2019.
Chapters from the book Big Crisis Data: Social Media in Disasters and Time-Critical Situations:
- 1) Ch3: "Vagueness: Natural language and semantics"
- 2) Ch4: "Variety: Classification and Clustering"
- 3) Ch11: "Values: Privacy and Ethics"
- 4) C.Rossia,⁎, F.S. Acerbob, K. Ylinenc, I. Jugac, P. Nurmic, A. Boscad, F. Tarasconid, M. Cristoforettie, A. Alikadic, 2018, Early detection and information extraction for weather-induced floods using social media streams, Journal of Disaster Risk Reduction, PP: 1--13, File:P4-2019.pdf
- 5) J. Rexiline Raginia, P.M. Rubesh Anandb,⁎, Vidhyacharan Bhaskarc, 2018, Big data analytics for disaster response and recovery through sentiment analysis, International Journal of Information Management, PP: 1--13, File:P5-2019.pdf
- 6) Deniz Kılınç, 2019, A Spark-based big data analysis framework for real-time sentiment prediction on streaming data, Jornal of Software, Practice and Experience, PP: 1--13, File:P6-2019.pdf
- 7) Francesco Tarasconi, Michela Farina, Antonio Mazzei, Alessio Bosca, 2017, The Role of Unstructured Data in Real-Time Disaster-related Social Media Monitoring, IEEE International Conference on Big Data, PP:1--10, File:P6a.pdf.
Suitable readings:
- Machine Learning Library (MLlib) Guide
- Spark Streaming Tutorial – Sentiment Analysis Using Apache Spark
- Artificial intelligence is finally getting smart
- Machine learning
- Data visualization on Tableau with Spark
- Spark MLlib
- Chapter and Paper presentations by you:
- Ch3: Martin Eidsvik Torvanger and Martin Skivenesvåg Johannessen
- Ch4: Ole Anders Smith and Øyvind Johannessen
- Ch11: Sindre Sperrud Kjær and Sølve Ånneland
- Paper 4: Stian Botnevik and Sunniva Blom Stolt-Nielsen
- Paper 5: Thomas Søvik and Tor Halvorsen Aasheim
- Paper 6: Tord Kvifte and Knut Asbjørn Troland Hufthammer
Slides: Session-6: [[:File:]]
Useful Links: