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dc.contributor.advisorFrédo Duranden_US
dc.contributor.authorLandman, Nathan, M. Eng. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-12-18T19:48:09Z
dc.date.available2018-12-18T19:48:09Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/119743
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 91-94).en_US
dc.description.abstractMachine understanding of text-based narratives have predominantly focused on documents with rigid hierarchical structures and sequentially ordered inputs. These inputs include documents such as news stories, encyclopedia entries, books, and many others. However, little research has focused on understanding text-based information without this structure. Current text understanding models fail when information is presented in less structured ways, without a clear and pre-defined spatial arrangement of the content. This thesis explores a subset of components required for understanding infographics -- documents whose structure is not necessarily linear and whose content may involve a variety of images. We expand on state-of-the-art methodologies in character recognition and text summarization in order to better understand how to process content without a pre-determined spatial arrangement, and subsequently generate captions for given infographics automatically. To shine light at the reasoning behind the captions being generated, we develop a graphical user interface that helps visualize the portions of a document being used when generating specific parts of a caption.en_US
dc.description.statementofresponsibilityby Nathan Landman.en_US
dc.format.extent94 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleTowards abstractive captioning of infographicsen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1078689853en_US


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