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Observing and optimizing online ad assignments

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TitleInfo
Title
Observing and optimizing online ad assignments
Name (type = personal)
NamePart (type = family)
Kruševskaja
NamePart (type = given)
Darja
NamePart (type = date)
1982-
DisplayForm
Darja Kruševskaja
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Muthukrishnan
NamePart (type = given)
S.
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S. Muthukrishnan
Affiliation
Advisory Committee
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chair
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Nath
NamePart (type = given)
Badri
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Badri Nath
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Advisory Committee
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internal member
Name (type = personal)
NamePart (type = family)
Farach-Colton
NamePart (type = given)
Martin
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Martin Farach-Colton
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Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Singer
NamePart (type = given)
Yaron
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Yaron Singer
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (encoding = w3cdtf); (qualifier = exact)
2015
DateOther (qualifier = exact); (type = degree)
2015-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2015
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
The main focus of this thesis work is on optimization and observation of ad assignments in online ad markets. Online ad markets allocate billions of impressions to advertisers while satisfying an array of constraints. Their revenues support the Internet ecosystem. They highlight theory problems and inspire systems research. In this thesis work we initiate the study that seeks to understand mechanisms and dynamics of advertising markets. We develop a scalable crawling capability that allows us to harvest a corpus of ads across a large number of websites and user profiles. We establish that user profile is essential in display ad markets: 50% of observed websites have at least 80% of their ads targeted at profiles. Further, we introduce cardinal auctions for selling multiple copies of a good, in which bidders specify not only their bid or how much they are willing to pay for the good, but also a cardinality constraint on the maximum size of the allocation in which they are willing to participate. We perform the first known analyses of Price of Anarchy and revenue of cardinal auctions. Finally, we introduce a new class of online allocation problems with secondary metrics, in which the goal is to optimize one metric (e.g., revenue), while meeting another (e.g., cost of user conversion). We suggest a number of theoretical approaches to the problem and test one of them in a real-world setting by using it in ad allocation in a ad network.
Subject (authority = RUETD)
Topic
Computer Science
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6803
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (ix, 91 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Internet advertising
Note (type = statement of responsibility)
by Darja Kruševskaja
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3JS9SD9
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Krusevskaja
GivenName
Darja
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-09-28 16:54:32
AssociatedEntity
Name
Darja Krusevskaja
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
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ETD
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windows xp
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