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Modeling users for online advertising
Descriptive
TitleInfo
Title
Modeling users for online advertising
Name
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NamePart
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Ma
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Qiang
NamePart
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1983-
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Qiang Ma
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author
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Muthukrishnan
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S.
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S. Muthukrishnan
Affiliation
Advisory Committee
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chair
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Rutgers University
Role
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degree grantor
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Graduate School - New Brunswick
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theses
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2016
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2016-10
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2016
Place
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xx
Language
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eng
Abstract
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Online advertising is able to target users at a fine level of granularity. To do this effectively, models are required to represent users and their behavior. In this thesis, we studied several problems related to models of online users. In online advertising, advertisers and ad platforms use user profiles as the language to target users, composed of user information from demographics, location, and interests. We implemented a user-profile-driven ad crawling framework and empirically investigated the relationship between user profiles and the ads to which they are exposed. We observed user profiles to play a greater role in display ads than in video ads. Furthermore, the main mode of accessing online content has been shifting from website browsing to mobile application usage. Mobile apps have become the building blocks to model user behavior on mobile devices. We designed a neural network model (app2vec) to vectorize mobile apps by studying how users employ these apps. We analyzed the learned app vectors qualitatively and quantitatively and used them to extract user app usage profiles for app-install advertising. Finally, advertisers are faced with the challenge of finding the optimal user profile properties to target. We designed a look-alike audience extension system, where advertisers provide a list of past converters as "seed users" and our system determines users similar to the seed. Rather than assuming linear separability of lookalike and non-lookalike users, as in prior work, we propose a new approach with nearest-neighbor filtering. Our system works efficiently for billions of users and improves the ad campaign conversion rate in practice at Yahoo!.
Subject
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Topic
Computer Science
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
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ETD
Identifier
ETD_7587
PhysicalDescription
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (xi, 104 p. : ill.)
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Subject
(authority = ETD-LCSH)
Topic
Human-computer interaction
Subject
(authority = ETD-LCSH)
Topic
Internet advertising
Subject
(authority = ETD-LCSH)
Topic
Internet marketing
Note
(type = statement of responsibility)
by Qiang Ma
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
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NjNbRU
Identifier
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doi:10.7282/T37S7R39
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Ma
GivenName
Qiang
Role
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Permission or license
DateTime
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2016-09-19 02:43:43
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Name
Qiang Ma
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Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
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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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2016-09-22T16:00:04
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2016-09-22T16:00:04
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