[CSEE-colloq] Martineau on domain adaptation for sentiment analysis, 1pm Fri 4 Nov, ITE227, UMBC

[Tim Finin]

                            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.