Brent Cochran


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Exploration and Discovery of the COVID-19 Literature through Semantic Visualization
Jingxuan Tu | Marc Verhagen | Brent Cochran | James Pustejovsky
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop

We propose semantic visualization as a linguistic visual analytic method. It can enable exploration and discovery over large datasets of complex networks by exploiting the semantics of the relations in them. This involves extracting information, applying parameter reduction operations, building hierarchical data representation and designing visualization. We also present the accompanying COVID-SemViz a searchable and interactive visualization system for knowledge exploration of COVID-19 data to demonstrate the application of our proposed method. In the user studies, users found that semantic visualization-powered COVID-SemViz is helpful in terms of finding relevant information and discovering unknown associations.

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Context-aware query design combines knowledge and data for efficient reading and reasoning
Emilee Holtzapple | Brent Cochran | Natasa Miskov-Zivanov
Proceedings of the 20th Workshop on Biomedical Language Processing

The amount of biomedical literature has vastly increased over the past few decades. As a result, the sheer quantity of accessible information is overwhelming, and complicates manual information retrieval. Automated methods seek to speed up information retrieval from biomedical literature. However, such automated methods are still too time-intensive to survey all existing biomedical literature. We present a methodology for automatically generating literature queries that select relevant papers based on biological data. By using differentially expressed genes to inform our literature searches, we focus information extraction on mechanistic signaling details that are crucial for the disease or context of interest.


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AskMe: A LAPPS Grid-based NLP Query and Retrieval System for Covid-19 Literature
Keith Suderman | Nancy Ide | Verhagen Marc | Brent Cochran | James Pustejovsky
Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020

In a recent project, the Language Application Grid was augmented to support the mining of scientific publications. The results of that ef- fort have now been repurposed to focus on Covid-19 literature, including modification of the LAPPS Grid “AskMe” query and retrieval engine. We describe the AskMe system and discuss its functionality as compared to other query engines available to search covid-related publications.