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Computational approaches for semantics-aware typographical choices
Descriptive
TitleInfo
Title
Computational approaches for semantics-aware typographical choices
Name
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NamePart
(type = family)
Kulahcioglu
NamePart
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Tugba
NamePart
(type = date)
1986-
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Tugba Kulahcioglu
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author
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de Melo
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Gerard
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Gerard de Melo
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Advisory Committee
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chair
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Boularias
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Abdeslam
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Abdeslam Boularias
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Advisory Committee
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internal member
Name
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Stone
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Matthew
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Matthew Stone
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Advisory Committee
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internal member
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(type = family)
Mihalcea
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Rada
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Rada Mihalcea
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Advisory Committee
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outside member
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Rutgers University
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degree grantor
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School of Graduate Studies
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school
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Text
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theses
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ETD doctoral
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2020
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2020-10
Language
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English
Abstract
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Typographic signals carry strong semantic connotations, e.g., they may convey excitement, anger or even sweetness, which empowers them to affect almost any aspect of life, from perception of an email, to the perceived sweetness of a cup of coffee. This thesis explores some of the possibilities that can be offered by computational approaches to support users in understanding and taking advantage of this impact. More specifically, the focus is on learning font semantics from crowdsourced and Web data, and using this information to facilitate font search and recommendation. Among the novel contributions are the use of CNN-based embeddings to represent fonts in attribute learning, leveraging emotion theories and lexical relations to infer font semantics, a multimodal font search method that allows specifying a reference font together with the target semantic additions, enabled by a cross-modal representation of fonts and words, and the proposal of affect-aware word clouds that let users specify a target emotion, which is used to recommend fonts and color palettes with congruent affective connotations.
Subject
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Topic
Typography
Subject
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Topic
Computer Science
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Rutgers University Electronic Theses and Dissertations
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ETD_11266
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application/pdf
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text/xml
Extent
1 online resource (vii, 118 pages) : illustrations
Note
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Ph.D.
Note
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier
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doi:10.7282/t3-p12c-4q57
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Kulahcioglu
GivenName
Tugba
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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2020-09-30 22:09:46
AssociatedEntity
Name
Tugba Kulahcioglu
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
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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.
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Embargo
DateTime
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2020-10-31
DateTime
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2021-05-02
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after May 2nd, 2021.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2020-10-01T02:06:13
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