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Anonymous Microsoft Web Data Data Set
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Abstract: Log of anonymous users of; predict areas of the web site a user visited based on data on other areas the user visited.

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Jack S. Breese, David Heckerman, Carl M. Kadie
Microsoft Research, Redmond WA, 98052-6399, USA
breese '@', heckerma '@', carlk '@'


Breese:, Heckerman, & Kadie

Data Set Information:

We created the data by sampling and processing the logs. The data records the use of by 38000 anonymous, randomly-selected users. For each user, the data lists all the areas of the web site (Vroots) that user visited in a one week timeframe.

Users are identified only by a sequential number, for example, User #14988, User #14989, etc. The file contains no personally identifiable information. The 294 Vroots are identified by their title (e.g. "NetShow for PowerPoint") and URL (e.g. "/stream"). The data comes from one week in February, 1998.

Attribute Information:

Each attribute is an area ("vroot") of the web site.

The datasets record which Vroots each user visited in a one-week timeframe in Feburary 1998.

Relevant Papers:

J. Breese, D. Heckerman., C. Kadie _Empirical Analysis of Predictive Algorithms for Collaborative Filtering_ Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July, 1998.
[Web Link]

Also, expanded as Microsoft Research Technical Report MSR-TR-98-12, The papers are available on-line at: [Web Link]

Papers That Cite This Data Set1:

Dmitry Pavlov and Jianchang Mao and Byron Dom. Scaling-Up Support Vector Machines Using Boosting Algorithm. ICPR. 2000. [View Context].

Kristin P. Bennett and Erin J. Bredensteiner. Geometry in Learning. Department of Mathematical Sciences Rensselaer Polytechnic Institute. [View Context].

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[1] Papers were automatically harvested and associated with this data set, in collaboration with

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