Name
Abstract | ||
|---|---|---|
Eliciting user preferences for large datasets and creating rankings based on these preferences has many practical applications in community-based sites. This paper gives a new method to elicit user preferences that does not ask users to tell what they prefer, but rather what a random person would prefer, and rewards them if their prediction is correct. We provide an implementation of our method as a two-player game in which each player is shown two images and asked to click on the image their partner would prefer. The game has proven to be enjoyable, has attracted tens of thousands of people and has already collected millions of judgments. We compare several algorithms for combining these relative judgments between pairs of images into a total ordering of all images and present a new algorithm to perform collaborative filtering on pair-wise relative judgments. In addition, we show how merely observing user preferences on a specially chosen set of images can predict a user's gender with high probability. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1518701.1518882 | CHI |
Keywords | Field | DocType |
relative judgment,user preference,two-player game,high probability,community-based site,pair-wise relative judgment,large datasets,eliciting user preference,new method,new algorithm,online game,collaborative filtering,total order | Preference elicitation,Ask price,Collaborative filtering,Computer science,Human computation,Human–computer interaction,Multimedia | Conference |
Citations | PageRank | References |
52 | 4.67 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Severin Hacker | 1 | 199 | 11.78 |
| Luis von Ahn | 2 | 3461 | 346.66 |