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http://aidr.qcri.org/
Muhammad Imran, Carlos Castillo, Ji Lucas,
Patrick Meier, Sarah Vieweg
Qatar Computing Research Inst...
http://aidr.qcri.org/
2013 Pakistan Earthquake: September 28 at 07:34 UTC 2010 Haiti Earthquake: January 12 at 21:53 UTC
C...
CRISIS COMPUTING
http://aidr.qcri.org/
Apply machine learningApply crowdsourcing
CRISIS COMPUTING: CHALLENGES
http://aidr.qcri.org/
- High velocity (e.g., 16k tweets / minute during Sandy)
- Redundant in...
http://aidr.qcri.org/
AIDR —Artificial Intelligence for Disaster Response— is a free, open-source, and easy-to-use
platfor...
ML+ CROWDSOURCING
http://aidr.qcri.org/
AIDR = Machine learning + Crowdsourcing
AIDR: FROM END-USERS PERSPECTIVE
Collection Classifier(s)
• Keywords, Hashtags
• Geographical bounding box
• Language
• Fo...
AIDR APPROACH
Collection Classifier(s)
Tag Tag
Tag Tag
Learner
Classifier-1
Tag
Tag Tag Tag
30k/min
Classifier-2
http://ai...
AIDR – COLLECTION SETUP
Collection detail dashboard
http://aidr.qcri.org/
Geographical region filterLanguage filter
Collec...
http://aidr.qcri.org/
AIDR – CLASSIFIER SETUP
AIDR – CLASSIFIER SETUP (cont.)
http://aidr.qcri.org/
AIDR – CROWDSOURCING-1
Internal Tagging Interface
http://aidr.qcri.org/
AIDR – CROWDSOURCING-2
MicroMapper Interface (browser clicker)
http://aidr.qcri.org/
Mobile clicker
AIDR – OUTPUT
http://aidr.qcri.org/
Training examples Classified output (achieved accuracy ~ 75%)
AIDR – CLASSIFICATION USING RANDOM FOREST
http://aidr.qcri.org/
T1 T2 T3 Tn
Features
Category a
Category b
Data: predictor...
http://aidr.qcri.org/
AIDR —Artificial Intelligence for Disaster Response— is a free, open-source, and easy-to-use
platfor...
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Artificial Intelligence for Disaster Response

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We present AIDR (Artificial Intelligence for Disaster Response), a platform designed to perform automatic classification of crisis-related microblog communications. AIDR enables humans and machines to work together to apply human intelligence to large-scale data at high speed. The objective of AIDR is to classify messages that people
post during disasters into a set of user-defined categories of information (e.g., “needs”, “damage”, etc.) For this purpose, the system continuously ingests data from Twitter, processes it (i.e., using machine learning classification techniques) and leverages human-participation (through crowdsourcing) in real-time. AIDR has been successfully tested to classify informative vs. non-informative tweets posted during the 2013 Pakistan Earthquake. Overall, we achieved a classification quality (measured using AUC) of 80%. AIDR is available at http://aidr.qcri.org/.

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Artificial Intelligence for Disaster Response

  1. 1. http://aidr.qcri.org/ Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, Sarah Vieweg Qatar Computing Research Institute (QCRI) Doha, Qatar AIDR: Artificial Intelligence for Disaster Response
  2. 2. http://aidr.qcri.org/ 2013 Pakistan Earthquake: September 28 at 07:34 UTC 2010 Haiti Earthquake: January 12 at 21:53 UTC CRISIS COMPUTING … Content generator Social Media Messages
  3. 3. CRISIS COMPUTING http://aidr.qcri.org/ Apply machine learningApply crowdsourcing
  4. 4. CRISIS COMPUTING: CHALLENGES http://aidr.qcri.org/ - High velocity (e.g., 16k tweets / minute during Sandy) - Redundant information (high volume of re-tweets) - Unstructured messages - Short text (140 characters in case of tweets) - Multilingual messages - Poor grammar
  5. 5. http://aidr.qcri.org/ AIDR —Artificial Intelligence for Disaster Response— is a free, open-source, and easy-to-use platform to automatically filter and classify relevant tweets posted during humanitarian crises.
  6. 6. ML+ CROWDSOURCING http://aidr.qcri.org/ AIDR = Machine learning + Crowdsourcing
  7. 7. AIDR: FROM END-USERS PERSPECTIVE Collection Classifier(s) • Keywords, Hashtags • Geographical bounding box • Language • Follow specific set of users A collection is a set of filters A classifier is a set of tags • Donations requests & offers • Damage & causalities • Eyewitness accounts 2 step approach 1 2 http://aidr.qcri.org/
  8. 8. AIDR APPROACH Collection Classifier(s) Tag Tag Tag Tag Learner Classifier-1 Tag Tag Tag Tag 30k/min Classifier-2 http://aidr.qcri.org/
  9. 9. AIDR – COLLECTION SETUP Collection detail dashboard http://aidr.qcri.org/ Geographical region filterLanguage filter Collection definition
  10. 10. http://aidr.qcri.org/ AIDR – CLASSIFIER SETUP
  11. 11. AIDR – CLASSIFIER SETUP (cont.) http://aidr.qcri.org/
  12. 12. AIDR – CROWDSOURCING-1 Internal Tagging Interface http://aidr.qcri.org/
  13. 13. AIDR – CROWDSOURCING-2 MicroMapper Interface (browser clicker) http://aidr.qcri.org/ Mobile clicker
  14. 14. AIDR – OUTPUT http://aidr.qcri.org/ Training examples Classified output (achieved accuracy ~ 75%)
  15. 15. AIDR – CLASSIFICATION USING RANDOM FOREST http://aidr.qcri.org/ T1 T2 T3 Tn Features Category a Category b Data: predictors with known response Goal: predict the response when it’s unknown (e.g., Hepatitis) Protein < 45.43 V = yesno Protein >= 26 X <= p
  16. 16. http://aidr.qcri.org/ AIDR —Artificial Intelligence for Disaster Response— is a free, open-source, and easy-to-use platform to automatically filter and classify relevant tweets posted during humanitarian crises. Thank you!

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