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dc.identifier.urihttp://hdl.handle.net/11401/77273
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.language.isoen_US
dc.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dc.typeDissertation
dcterms.abstractTruly understanding natural language requires grounding language to perceptions and actions in the physical and social world. This goes beyond studying the textual modality alone. Today's web not only has sheer volume of data, but also increasingly multi-modal data, intertwining text with videos, images, audios, and ontologies that are perceptions or abstractions of people's everyday life. Hence the web provides rich and ever growing resources for studying grounded language. This thesis presents a series of investigations of language woven into various types of online data, ranging from ontology and images to time series. We contribute data distillation approaches and large-scale datasets connecting language to vision, a collection of models and algorithms, and multiple novel applications in hierarchical product classification, image description, and photo album summarization.
dcterms.available2017-09-20T16:52:19Z
dcterms.contributorWarren, Daviden_US
dcterms.contributorWarren, David Sen_US
dcterms.contributorFodor, Paulen_US
dcterms.contributorRamakrishnan, I.V.en_US
dcterms.contributorChoi, Yejinen_US
dcterms.contributorHajishirzi, Hannaneh.en_US
dcterms.creatorChen, Jianfu
dcterms.dateAccepted2017-09-20T16:52:19Z
dcterms.dateSubmitted2017-09-20T16:52:19Z
dcterms.descriptionDepartment of Computer Science.en_US
dcterms.extent93 pg.en_US
dcterms.formatMonograph
dcterms.formatApplication/PDFen_US
dcterms.identifierhttp://hdl.handle.net/11401/77273
dcterms.issued2015-12-01
dcterms.languageen_US
dcterms.provenanceMade available in DSpace on 2017-09-20T16:52:19Z (GMT). No. of bitstreams: 1 Chen_grad.sunysb_0771E_12566.pdf: 11778509 bytes, checksum: 0eed936a3cbf34c61d31b5daa841435a (MD5) Previous issue date: 1en
dcterms.publisherThe Graduate School, Stony Brook University: Stony Brook, NY.
dcterms.subjectComputer science
dcterms.subjectbig data, computer vision, language grounding, Natural Langue Processing, web
dcterms.titleLanguage Grounding in Massive Online Data
dcterms.typeDissertation


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