Microsoft Technology Licensing, LLC

Zhuoqing Wu, Jr

Shaoyu Zhou

Michael Elizarov

Siddhartha Roy

Fei Cao

Sijian Zhang

Large sets of unorganized data may provide little value in identifying useful observations from such data. For example, an online merchant may maintain a database of millions of user IDs (e.g., a cookie ID, a login ID, a device ID, a network ID, etc.) along with content viewed and/or actions taken with the user IDs, where minimal associations are known between user IDs. It may be advantageous to link together user IDs of respective users to capture a comprehensive view of respective users' activities. Accordingly, one or more systems and/or techniques for identifying a cluster of nodes based upon transforming a set of node pairings (e.g., pairings of related nodes) one or more times are disclosed herein. Iterative transformations may be performed until respective nodes are paired with merely their smallest neighboring node and are paired with no other node. In this way, node clusters may be identifiable.

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Bellevue, WA, United States of America

Zhuoqing Wu, Jr