1. SIGIR 2008 Yandong Liu, Jiang Bian, Eugene Agichtein from Emory & Georgia Tech University

7. Definition

9. Features  Question  Question-Answer Relationship  Asker User History  Answerer User History  Category Features  Textual Features

11. Formally a two-class classification problem but primarily focus on the satisfied class.

12.  Amazon’s paid rater service  Mechanical Turk

13. Datasets

14. Setting  Methods  Human  Heuristic  Baseline  Evaluation Metrics  Precision  Recall  F1  Accuracy  ASP  ASP_SVM  ASP_RandomForest  ASP_C4.5  ASP_Boosting  ASP_NaiveBayes

15. Result

16. Selected features

17.  Online vs. Offline

18.  Feature Ablation

19.  Textual Features

20.  Past Experience

21. Conclusion  First to quantify and predict asker satisfaction  Shown importance of asker history is this  Our system outperform human assessors