On this page we provide additional resources related
to the above mentioned paper. The resources include
experiment details, datasets to download, further
analyses and algorithms.
Currently, the paper is in the reviewing process and
from obvious reasons we provide only previews
of the files at the moment.
Experiment #1
Experiment #2 (textual mode)
Experiment #3 (card-based mode)
Experiment #4
Experiment #5 (top category)
Experiment #6 (second category)
Overview table:
Experiment | #Tasks | Workers/task | Payment/task | Worker satisfection | Payment total | Download dataset |
---|---|---|---|---|---|---|
#1 | 9 | 30 | 10.0 ¢ | 86.0% | \$ 27 | download |
#2 | 1125 | 5 | 0.60 ¢ | 68.0% | \$ 34 | download |
#3 | 1125 | 5 | 0.60 ¢ | 66.9% | \$ 34 | download |
#4 | 335 | 9 | 2.00 ¢ | 84.0% | \$ 60 | download |
#5 | 1148 | 5 | 0.75 ¢ | 60.0% | \$ 43 | download |
#6 | 1240 | 3 | 0.75 ¢ | 72.0% | \$ 28 | download |
Total | \$ 226 | download all |
We retrieved query suggestions for a sample of Foursquare POIs (see Section 3.2.1). Here we provide this data after cleansing steps described in the paper.
As described in Section 3.3.2, we normalized information needs extracted from Google Suggestions. Clustering provided by 3 assessors as well as final canonical set is made available here.
Author: Dingqi Yang
Download at: https://sites.google.com/site/yangdingqi/home/foursquare-dataset