Wanted: “Yahoo! Front Page Today Module User Click Log Dataset”

[jaberg]

For the wish list:

Dear colleagues,

I’m happy to announce the release of a new benchmark dataset (“Yahoo! Front Page Today Module User Click Log Dataset”) for unbiased evaluation of multi-armed bandit algorithms, through the Yahoo! Webscope Program: http://webscope.sandbox.yahoo.com/catalog.php?datatype=r

Due to the inherent interactive nature of bandit problems, creating a benchmark dataset for reliable algorithm evaluation is not as straightforward as in most other fields of machine learning, whose objectives are often prediction. This challenge is also known as off- policy reinforcement learning.

Our dataset contains the click log of over 45M user visits to the Featured Tab of the Today Module on Yahoo! Front Page. The articles were chosen uniformly at random to the users, which enables the use of an unbiased offline evaluation method recently shown to be highly effective [http://portal.acm.org/citation.cfm?doid=1935826.1935878]. To the best of our knowledge, this is the first benchmark for evaluating bandit algorithms reliably in real-world applications.

Lihong Li

Yahoo! Research 4401 Great America Parkway Santa Clara, CA, 95054 http://www.cs.rutgers.edu/~lihong

[Michael-Yi-Rong]

Dear professor, I applied for the dataset with my university email, but no response.