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Webpage design optimization using ge...

Park, Sunyoung.

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Webpage design optimization using genetic algorithm driven CSS.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Webpage design optimization using genetic algorithm driven CSS./
Author:	Park, Sunyoung.
Description:	102 p.
Notes:	Adviser: Sunghyun Ryoo Kang.
Contained By:	Masters Abstracts International45-05.
Subject:	Design and Decorative Arts. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1443081

Webpage design optimization using genetic algorithm driven CSS.
Park, Sunyoung.

Webpage design optimization using genetic algorithm driven CSS. - 102 p.

Adviser: Sunghyun Ryoo Kang.

Thesis (M.F.A.)--Iowa State University, 2007.

In the rapid emergence of globalization, e-commerce, and internet accessibility in remote parts of the world, ongoing feedback and participation from site visitors are essential for attaining clear and effective communication on a web site. This thesis presents a computational experiment for optimizing design of a webpage in an evolutionary manner. Webpage personalization is viewed as a configuration problem whose goal is to determine the optimal presentation of a webpage while taking into account the preference of the web author (designer), layout constraints (web design/editing language: HTML, CSS), and viewer interaction with the browser. The study proposes use of genetic algorithm-driven Cascading Style Sheets (CSS) to assist the process of webpage design optimization. This method will engage visitors to remotely modify and enhance the style (type, layout and color) of web site to fit their aesthetic and functional representation of well-received design. The preference feedback from user will be stored in an application server for automated evolutionary selection process and reinitialized for the next generation of users. Through the experimentation of web prototype and user evaluation test, the implementation of this method is examined and the derived design solutions are analyzed based on web aesthetics, standards, and accessibility.Subjects--Topical Terms:

1024640
Design and Decorative Arts.

Webpage design optimization using genetic algorithm driven CSS.
LDR:02161nam 2200253 a 45 001 973407
005 20110928
008 110928s2007 eng d
035 $a (UMI)AAI1443081
035 $a AAI1443081
040 $a UMI $c UMI
100 1 $a Park, Sunyoung. $3 1297359
245 1 0 $a Webpage design optimization using genetic algorithm driven CSS.
300 $a 102 p.
500 $a Adviser: Sunghyun Ryoo Kang.
500 $a Source: Masters Abstracts International, Volume: 45-05, page: 2111.
502 $a Thesis (M.F.A.)--Iowa State University, 2007.
520 $a In the rapid emergence of globalization, e-commerce, and internet accessibility in remote parts of the world, ongoing feedback and participation from site visitors are essential for attaining clear and effective communication on a web site. This thesis presents a computational experiment for optimizing design of a webpage in an evolutionary manner. Webpage personalization is viewed as a configuration problem whose goal is to determine the optimal presentation of a webpage while taking into account the preference of the web author (designer), layout constraints (web design/editing language: HTML, CSS), and viewer interaction with the browser. The study proposes use of genetic algorithm-driven Cascading Style Sheets (CSS) to assist the process of webpage design optimization. This method will engage visitors to remotely modify and enhance the style (type, layout and color) of web site to fit their aesthetic and functional representation of well-received design. The preference feedback from user will be stored in an application server for automated evolutionary selection process and reinitialized for the next generation of users. Through the experimentation of web prototype and user evaluation test, the implementation of this method is examined and the derived design solutions are analyzed based on web aesthetics, standards, and accessibility.
590 $a School code: 0097.
650 4 $a Design and Decorative Arts. $3 1024640
690 $a 0389
710 2 0 $a Iowa State University. $3 1017855
773 0 $t Masters Abstracts International $g 45-05.
790 $a 0097
790 1 0 $a Kang, Sunghyun Ryoo, $e advisor
791 $a M.F.A.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1443081