In this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constr...
Annotating genes and their products with Gene Ontology codes is an important area of research. One approach for doing this is to use the information available about these genes in...
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
This paper explores correspondence and mixture topic modeling of documents tagged from two different perspectives. There has been ongoing work in topic modeling of documents with...