event thumbnail image
Machine Learning Summer School 2006 - Taipei
Pascal

Ranking by Stealing Human Cycles

author: Tingfan Wu, UCSD

Description

Ranking objects is a challenging task for machines. The main difficulty is that some characteristics of interest lack objective criteria. As the Internet becomes more widely used, it is possible to integrate the human capability of evaluating unmeasurable properties with the computational power of machines. A good example is the Internet voting for photos, foods and many others. In this talk, we propose a paired comparison framework, in which users are asked to show preferences in a pair of objects. Experiments on a photo ranking task show that the paired method outperforms the commonly used scoring method.

You might be experiencing some problems with Your Video player.
Slides
0:05 Ranking by Stealing Human Cycles
0:23 The Problem
1:45 Hot or Not: Score 1 to 10
2:27 Drawbacks of Scoring Method
4:46 Drawbacks of Scoring Method 01
5:34 New Challenges
8:10 Design of The System
9:55 Paired Comparison Method
10:49 Experiment Design : Evaluation
12:45 Experiment Result
14:16 Conclusion

Lecture rating

People found this lecture:
Worth seeing
because it is:
 Valuable and informative
Well presented
Easily understandable
Acceptably recorded
You need to login to cast your vote.

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment: