Learning to Rank Scientific Documents from the Crowd
Table 4: Results for the model trained using the Google Scholar Related Articles ranking. We find that building a model using Google Scholar’s Related Articles ranking to predict our authors’ rankings performs poorly compared to the other models.
['Training Set', 'Test Set', 'NDCG', 'Kendall’s  [ITALIC] τ', '[ITALIC] τap']
Next we compare our model to Google Scholar ’s rankings. Using the ranking collected from Google Scholar, we build a training set to try to predict our authors’ rankings. We find that Google Scholar performs similarly to the text-only features model. This indicates that the rankings we obtained from the authors are substantially different than the rankings that Google Scholar provides.