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Ana Lucic
Researcher at University of Illinois at Urbana–Champaign
Publications - 17
Citations - 64
Ana Lucic is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Noun & Support vector machine. The author has an hindex of 5, co-authored 16 publications receiving 56 citations. Previous affiliations of Ana Lucic include DePaul University.
Papers
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Journal ArticleDOI
Automatic endpoint detection to support the systematic review process
Catherine Blake,Ana Lucic +1 more
TL;DR: A two-step approach is introduced to automatically extract three facets - two entities (the agent and object) and the way in which the entities are compared (the endpoint) from direct comparative sentences in full-text articles to accelerate the systematic review process and identify gaps where future research should be focused.
Journal ArticleDOI
A syntactic characterization of authorship style surrounding proper names
Ana Lucic,Catherine Blake +1 more
TL;DR: A new high-level feature based on local syntactic dependencies that an author uses when referring to a named entity (in this case a person’s name) is introduced and a series of experiments reveal how the amount of data in both the training and test sets influences predictive performance.
Reading Chicago Reading: Quantitative Analysis of a Repeating Literary Program.
TL;DR: This essay presents quantitative capture and predictive modeling for one of the largest and longest running mass reading programs of the past two decades: “One Book One Chicago” (OBOC) sponsored by the Chicago Public Library (CPL).
Proceedings Article
Improving Endpoint Detection to Support Automated Systematic Reviews.
Ana Lucic,Catherine Blake +1 more
TL;DR: It is shown empirically that establishing if head noun is an amount or measure provides a statistically significant improvement that increases the endpoint precision from 0.42 to 0.56 on longer and from0.51 to0.58 on shorter sentences and recall.
A Method to Automatically Identify the Results from Journal Articles
TL;DR: This paper focuses on the identification of any claim in an article and on the Identification of explicit claims, a subtype of a more general claim, and frames the problem as a classification task and employs three different domainindependent feature selection strategies.