We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Analyzing the author and topic relations in email corpus is an important issue in both social network analysis and text mining. The AuthorTopic model is a statistical model that id...
Abstract. Topic models are a discrete analogue to principle component analysis and independent component analysis that model topic at the word level within a document. They have ma...
We present a domain-independent unsupervised topic segmentation approach based on hybrid document indexing. Lexical chains have been successfully employed to evaluate lexical cohe...
Word prediction can be used for enhancing the communication ability of persons with speech and language impairments. In this work, we explore two methods of adapting a language mo...
Keith Trnka, Debra Yarrington, Kathleen F. McCoy, ...