talk: Martineau on domain adaptation for sentiment analysis

Sun, 30 Oct 2011 21:26:12 -0400
graduate, news, nlp, research, sentiment, talks

CSEE Colloquium

Identifying and Isolating Text Classification Signals from
Domain and Genre Noise for Sentiment Analysis

Justin Martineau
Computer Science and Electrical Engineering
University of Maryland, Baltimore County

1:00pm Friday 4 November 2011, ITE 227

Justin Martineau will describe the results of his PhD dissertation which he will defend later this month. His dissertation research makes both algorithmic and theoretical contributions to the fields of domain adaption and sentiment analysis. First, it provides algorithms to discover and weight discriminative classification task specific features within a domain. Second, it produces algorithms to score how well these features transfer to a new target domain. Third, it lays out a general theory for the kinds of information and the types of noise they produce that exist in text classification tasks. Finally, the dissertation presents a definition of domain independence and a statistical description of it. The research offers readers a firm theoretical foundation as well as practical algorithms when implementing any of the motivating examples and for future research in the field.