Practical guide to controlled experiments on the web: listen to your customers not to the hippo
By Ron Kohavi, Randal M. Henne, Randal M. Henne, Dan Sommerfield. 2007
400 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Statistics and Probability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- John Riedl
- J. Konstan
- Michael D. Ekstrand
- Sudipta Sengupta
- Jeffrey Heer
- Michael Bostock
- Mohammad Alizadeh
- Nava Tintarev
In Information Systems
- Michael D. Ekstrand
- John Riedl
- J. Konstan
- Mohammad Alizadeh
- David A. Maltz
- Albert G. Greenberg
- Jeffrey Heer
- Gediminas Adomavicius
In Statistics and Probability
Citations in the corpus
- Collaborative Filtering Recommender Systems (2011, background): “Field trials, frequently in the form of A/B tests, are commonly used in commercial recommender deployments where sites have already established user bases and can test a new algorithm or other site change on a small subset of their users [76, 77].”
- The cost of a cloud: research problems in data center networks (2008, background): “There is substantial empirical evidence suggesting that performance directly impacts revenue [22].”
- Data center TCP (DCTCP) (2010, background): “For interactive, soft-real-time applications like these, latency is the key metric, with total permissible latency being determined by factors including customer impact studies [21].”
- Automatically generating personalized user interfaces with Supple (2010, neutral): “[43] offer some helpful initial insights.”
- WTF: the who to follow service at Twitter (2013, neutral): “, [14] for more discussion.”
- Crowdsourcing graphical perception: using mechanical turk to assess visualization design (2010, background): “[15] provide a brief survey of experiments and recommendations for web experiment design.”