Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
The SLIF project combines text-mining and image processing to extract structured information from biomedical literature. SLIF extracts images and their captions from published pap...
This paper presents a statistical model for discovering topical clusters of words in unstructured text. The model uses a hierarchical Bayesian structure and it is also able to iden...
In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify ...
In this paper, we define and study a new opinionated text data analysis problem called Latent Aspect Rating Analysis (LARA), which aims at analyzing opinions expressed about an e...