Multiview Rank Learning for Multimedia Known Item Search

dc.contributor.advisor	Domeniconi, Carlotta
dc.contributor.author	Etter, David
dc.creator	Etter, David
dc.date.accessioned	2015-07-29T18:42:49Z
dc.date.available	2015-07-29T18:42:49Z
dc.date.issued	2015
dc.identifier.uri	https://hdl.handle.net/1920/9698
dc.description.abstract	Known Item Search (KIS) is a specialized task of the general multimedia search problem. KIS describes the scenario where a user has seen a video before, must formulate a text description based on what he remembers, and knows that there is only one correct answer. The KIS task takes as input a text-only description and returns the ranked list of videos most likely to match the known item.
dc.format.extent	123 pages
dc.language.iso	en
dc.rights	Copyright 2015 David Etter
dc.subject	Multimedia	en_US
dc.subject	Computer science	en_US
dc.subject	Known Item Search	en_US
dc.subject	Multimedia	en_US
dc.subject	Multiview	en_US
dc.subject	Ranking	en_US
dc.title	Multiview Rank Learning for Multimedia Known Item Search
dc.type	Dissertation	en
thesis.degree.level	Doctoral	en
thesis.degree.discipline	Computational Science	en
thesis.degree.grantor	George Mason University	en