Výsledky vyhledávání - "HIRSCHMAN, LYNETTE"

Report

Final Report on MITRE Evaluations for the DARPA Big Mechanism Program

Autor: Peterson, Matthew, Korves, Tonia, Garay, Christopher, Kozierok, Robyn, Hirschman, Lynette

This report presents the evaluation approach developed for the DARPA Big Mechanism program, which aimed at developing computer systems that will read research papers, integrate the information into a computer model of cancer mechanisms, and frame new

Externí odkaz: http://arxiv.org/abs/2211.03943

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Report

Hallmarks of Human-Machine Collaboration: A framework for assessment in the DARPA Communicating with Computers Program

Autor: Kozierok, Robyn, Aberdeen, John, Clark, Cheryl, Garay, Christopher, Goodman, Bradley, Korves, Tonia, Hirschman, Lynette, McDermott, Patricia L., Peterson, Matthew W.

There is a growing desire to create computer systems that can communicate effectively to collaborate with humans on complex, open-ended activities. Assessing these systems presents significant challenges. We describe a framework for evaluating system

Externí odkaz: http://arxiv.org/abs/2102.04958

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Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup

Autor: Yeh, Alexander S., Hirschman, Lynette, Morgan, Alexander A.

Publikováno v: Bioinformatics Vol. 19 Suppl. 1 2003, pages i331-i339

MOTIVATION: The biological literature is a major repository of knowledge. Many biological databases draw much of their content from a careful curation of this literature. However, as the volume of literature increases, the burden of curation increase

Externí odkaz: http://arxiv.org/abs/cs/0308032

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How to Evaluate your Question Answering System Every Day and Still Get Real Work Done

Autor: Breck, Eric, Burger, John D., Ferro, Lisa, Hirschman, Lynette, House, David, Light, Marc, Mani, Inderjeet

In this paper, we report on Qaviar, an experimental automated evaluation system for question answering applications. The goal of our research was to find an automatically calculated measure that correlates well with human judges' assessment of answer

Externí odkaz: http://arxiv.org/abs/cs/0004008

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Akademický článek

Automatic classification of RDoC positive valence severity with a neural network

Autor: Clark, Cheryl, Wellner, Ben, Davis, Rachel, Aberdeen, John, Hirschman, Lynette

Publikováno v: In Journal of Biomedical Informatics November 2017 75 Supplement:S120-S128

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Report

Automating Coreference: The Role of Annotated Training Data

Autor: Hirschman, Lynette, Robinson, Patricia, Burger, John, Vilain, Marc

We report here on a study of interannotator agreement in the coreference task as defined by the Message Understanding Conference (MUC-6 and MUC-7). Based on feedback from annotators, we clarified and simplified the annotation specification. We then p

Externí odkaz: http://arxiv.org/abs/cmp-lg/9803001

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