My research has covered a broad range of topics in applied computational linguistics and natural language processing. They include: lexical semantics; the resolution of ambiguity in text; the analysis of authors’ styles in literature and other text (including plagiarism detection and the detection of online sexual predators) and the preservation of an author’s style in machine translation; recovering from misunderstanding and non-understanding in human-computer communication; linguistic constraints on knowledge-representation systems; the problem of near-synonymy in lexical choice in language generation; applications of lexical chaining as an indicator of semantic distance in texts; detecting markers of Alzheimer's disease in language; determining ideology in political texts; and the identification of the native language of a second-language writer of English. With colleagues in Canada, the U.K. and the Netherlands, I was a co-PI of a Digging Into Data grant on processing linked parliamentary data.
Current and recent research topics
Determing causes of death from verbal autopsies
Detecting Alzheimer’s disease, aphasia, and cognitive decline in writing and speech
Lexical nuances of style and meaning
Discourse coherence and rhetorical parsing
Automatic discrimination of authorship, including the detection of plagiarism and sexual predation
Digitizing and analyzing Parliamentary proceedings
Theoretical issues of meaning and representation in computational linguistics
Argument mining; analyzing the framing of issues; determining a speaker's ideology
Computational analysis of literature
Some past projects
Medical question-answering at the point of care
Intelligent real-word spelling correction
Syntactic nuances of style and meaning
Finding and applying threads of meaning in documents
Discourse structure, rhetorical parsing, and text summarization
Graeme Hirst
Professor of Computational Linguistics
Research