Three methods for combining multiple clustering systems are presented and evaluated, focusing on the problem of finding the correspondence between clusters of different systems. ...
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
Most queries in web search are ambiguous and multifaceted. Identifying the major senses and facets of queries from search log data, referred to as query subtopic mining in this pa...
Yunhua Hu, Ya-nan Qian, Hang Li, Daxin Jiang, Jian...
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...