All kinds of phenomena interest me, but I'm more interested in experimental science than theoretical, and more interested in pure science than applied. Theory is important, but I don't have much patience for drifting away from testability. Applications are important, but it's the big questions that get me excited.
My current projects include:
At an internship with Beth Sundheim at SPAWAR, I worked on several projects related to multi-lingual text processing and named entity recognition, including a study derived from the TDT 2002 link detection task, comparing the relative value of general lexical features, temporal expressions, and named entities for the identification of event-based topics, and comparing the published temporal expression vector spaces to some I developed.
Lucien Carroll. 2005. Topic Detection Using Time Expressions. Work carried out under the supervision of Beth Sundheim, as part of an internship with the SDSU Research Foundation.
In collaboration with Erin Stevenson and Rebecca Colavin, I worked on developing a system to distinguish degrees of bias in politically oriented websites, approaching it from two directions: as a language classification problem, like distinguishing subjective language from objective language; and as a network partitioning problem, using position within the hyperlink network to identify affiliation. We harvested the test corpus from the internet, and hand-annotated the target classes. For the linguistic approach we used standard machine learning methods with linguistically-informed features, and for the network approach we used mathematical methods from social network analysis.
Lucien Carroll, Erin Stevenson, and Rebecca Colavin. 2005. Website Bias Estimation with Combined Language Modeling and Network Analysis. Work carried out under the supervision of Rob Malouf. Presented by Erin at the 28th Linguistics Students Association Colloquium at SDSU, April 16, 2005. slides other slides
Hannah Rohde, Rebecca Colavin, Lara Taylor and I worked on the problem of semantic role labeling, as proposed in the CoNLL 2005 Shared Task. We implemented a system that derived a wide variety of rule-based syntactic and semantic features for the sentences in the CoNLL 2005 corpus, to train a conditional random fields model of the target series of semantic role labels.
Hannah Rohde, Lucien Carroll, Rebecca Colavin, and Lara Taylor. 2005. Head-Noun Proto-Properties for Semantic Role Labeling. Part of an attempted entry in the CoNLL 2005 Shared Task, under the supervision of Rob Malouf. Presented by Hannah at the 28th Linguistics Students Association Colloquium at SDSU, April 16, 2005. slides