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dc.contributor.advisorRegina Barzilay.en_US
dc.contributor.authorSoetjipto, Rusminen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2014-03-06T15:46:35Z
dc.date.available2014-03-06T15:46:35Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/85501
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 61-62).en_US
dc.description.abstractWe demonstrated the possibility of inferring the research interest of an MIT faculty member given the title of only a few research papers written by him or her, using a topic model learned from a corpus of research paper text not necessarily related to any faculty members of MIT, and a list of topic keywords such as that of the Library of Congress. The topic model was generated using a variant of Latent Dirichlet Allocation coupled with a pointwise mutual information analysis between topic keywords and latent topics.en_US
dc.description.statementofresponsibilityby Rusmin Soetjipto.en_US
dc.format.extent62 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleAutomatic detection of research interest using topic modelingen_US
dc.title.alternativeName disambiguation in MIT collaboration browseren_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc871003259en_US


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