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Henry A. Lieberman. Henke, Joseph D Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2014-11-24T18:37:41Z 2014-11-24T18:37:41Z 2014 2014 http://hdl.handle.net/1721.1/91826 894226590 Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. Cataloged from PDF version of thesis. Includes bibliographical references (pages 75-76). Common Sense Inference is an increasingly attractive technique to make computer interfaces more in touch with how human users think. However, the results of the inference process are often hard to interpret and evaluate. Visualization has been successful in many other fields of science, but to date it has not been used much for visualizing the results of inference. This thesis presents Alar, an interface which allows dynamic exploration of the results of the inference process. It enables users to detect errors in the input data and fine tune how liberal or conservative the inference should be. It accomplishes this through novel extensions to the AnalogySpace framework for inference and visualizing concepts and even assertions as nodes in a graph, clustered by their semantic relatedness. A usability study was performed and the results show users were able to successfully use Alar to determine the cause of an incorrect inference. by Joseph D. Henke. M.Eng. 76 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Visualizing inference Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="64c5cfd9-5aa6-49aa-97f1-ba52c014aa90"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Visualizing inference</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2014</PublicationDate> <Authors> <Author> <DisplayName>Henke, Joseph D</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Common Sense Inference is an increasingly attractive technique to make computer interfaces more in touch with how human users think. However, the results of the inference process are often hard to interpret and evaluate. Visualization has been successful in many other fields of science, but to date it has not been used much for visualizing the results of inference. This thesis presents Alar, an interface which allows dynamic exploration of the results of the inference process. It enables users to detect errors in the input data and fine tune how liberal or conservative the inference should be. It accomplishes this through novel extensions to the AnalogySpace framework for inference and visualizing concepts and even assertions as nodes in a graph, clustered by their semantic relatedness. A usability study was performed and the results show users were able to successfully use Alar to determine the cause of an incorrect inference.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>