An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
In this paper, we propose a new way to automatically model and predict human behavior of receiving and disseminating information by analyzing the contact and content of personal c...
Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming...
Readability is a crucial presentation attribute that web summarization algorithms consider while generating a querybaised web summary. Readability quality also forms an important ...