We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is ty...
We present an automated ontology matching methodology, supported by various machine learning techniques, as implemented in the system MoTo. The methodology is twotiered. On the ï¬...
We describe Glosser, a system that supports students in writing essays by 1) scaffolding their reflection with trigger questions, and 2) using text mining techniques to provide co...