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Hierarchical composable optimization of web pages

Published: 16 April 2012 Publication History

Abstract

The process of creating modern Web media experiences is challenged by the need to adapt the content and presentation choices to dynamic real-time fluctuations of user interest across multiple audiences. We introduce FAME -- a Framework for Agile Media Experiences -- which addresses this scalability problem. FAME allows media creators to define abstract page models that are subsequently transformed into real experiences through algorithmic experimentation. FAME's page models are hierarchically composed of simple building blocks, mirroring the structure of most Web pages. They are resolved into concrete page instances by pluggable algorithms which optimize the pages for specific business goals. Our framework allows retrieving dynamic content from multiple sources, defining the experimentation's degrees of freedom, and constraining the algorithmic choices. It offers an effective separation of concerns in the media creation process, enabling multiple stakeholders with profoundly different skills to apply their crafts and perform their duties independently, composing and reusing each other's work in modular ways.

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Cited By

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  • (2020)Dynamic Creative Optimization in Verizon Media Native Advertising2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9378251(1654-1662)Online publication date: 10-Dec-2020
  • (2019)Carousel Ads Optimization in Yahoo Gemini NativeProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330740(1993-2001)Online publication date: 25-Jul-2019
  • (2017)Automatic Generation of User Interface Layouts for Alternative Screen OrientationsHuman-Computer Interaction - INTERACT 201710.1007/978-3-319-67744-6_2(13-35)Online publication date: 20-Sep-2017

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Published In

cover image ACM Other conferences
WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web
April 2012
1250 pages
ISBN:9781450312301
DOI:10.1145/2187980
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • Univ. de Lyon: Universite de Lyon

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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Author Tags

  1. multivariate testing
  2. web page optimization framework

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  • Research-article

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WWW 2012
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  • Univ. de Lyon
WWW 2012: 21st World Wide Web Conference 2012
April 16 - 20, 2012
Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all
  • (2020)Dynamic Creative Optimization in Verizon Media Native Advertising2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9378251(1654-1662)Online publication date: 10-Dec-2020
  • (2019)Carousel Ads Optimization in Yahoo Gemini NativeProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330740(1993-2001)Online publication date: 25-Jul-2019
  • (2017)Automatic Generation of User Interface Layouts for Alternative Screen OrientationsHuman-Computer Interaction - INTERACT 201710.1007/978-3-319-67744-6_2(13-35)Online publication date: 20-Sep-2017

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