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KDD
2005
ACM

Cross-relational clustering with user's guidance

13 years 9 months ago
Cross-relational clustering with user's guidance
Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information often spreads across multiple relations. To ensure effective and efficient high-dimensional, cross-relational clustering, we propose a new approach, called CrossClus, which performs cross-relational clustering with user’s guidance. We believe that user’s guidance, even likely in very simple forms, could be essential for effective high-dimensional clustering since a user knows well the application requirements and data semantics. CrossClus is carried out as follows: a user specifies a clustering task and selects one or a small set of features pertinent to the task. CrossClus extracts the set of highly relevant features in multiple relations connected via linkages defined in the database schema, evaluates their effectiveness based on user’s guidance, and identifies interesting clusters that fit user...
Xiaoxin Yin, Jiawei Han, Philip S. Yu
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where KDD
Authors Xiaoxin Yin, Jiawei Han, Philip S. Yu
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