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Using link analysis to improve layout on mobile devices

Published: 17 May 2004 Publication History

Abstract

Delivering web pages to mobile phones or personal digital assistants has become possible with the latest wireless technology. However, mobile devices have very small screen sizes and memory capacities. Converting web pages for delivery to a mobile device is an exciting new problem. In this paper, we propose to use a ranking algorithm similar to Google's PageRank algorithm to rank the content objects within a web page. This allows the extraction of only important parts of web pages for delivery to mobile devices. Experiments show that the new method is effective. In experiments on pages from randomly selected websites, the system needed to extract and deliver only 39% of the objects in a web page in order to provide 85% of a viewer's desired viewing content. This provides significant savings in the wireless traffic and downloading time while providing a satisfactory reading experience on the mobile device.

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cover image ACM Conferences
WWW '04: Proceedings of the 13th international conference on World Wide Web
May 2004
754 pages
ISBN:158113844X
DOI:10.1145/988672
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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Publication History

Published: 17 May 2004

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Author Tags

  1. html
  2. link analysis
  3. pda (personal digital assistant)
  4. www (world wide web)

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

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Cited By

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  • (2023)Optical Character Recognition (OCR)-Based and Gaussian Mixture Modeling-OCR-Based Slide-Level “With-Me-Ness”: Automated Measurement and Feedback of Learners’ Attention State during Video LecturesInternational Journal of Human–Computer Interaction10.1080/10447318.2023.220427240:15(3952-3971)Online publication date: 7-May-2023
  • (2021)Content-Determined Web Page Segmentation and Navigation for Mobile Web SearchingResult Page Generation for Web Searching10.4018/978-1-7998-0961-6.ch007(88-108)Online publication date: 2021
  • (2021)Transcoding web pages via stylesheets and scripts for saving energy on the clientSoftware: Practice and Experience10.1002/spe.304652:4(984-1003)Online publication date: 20-Oct-2021
  • (2020)“The Best of Both Worlds!”ACM Transactions on the Web10.1145/337249714:1(1-31)Online publication date: 9-Jan-2020
  • (2019)Alternative Nonvisual Web Browsing TechniquesWeb Accessibility10.1007/978-1-4471-7440-0_32(629-649)Online publication date: 4-Jun-2019
  • (2018)An Automatic e-news Article Content Extraction and Classification2018 18th International Conference on Advances in ICT for Emerging Regions (ICTer)10.1109/ICTER.2018.8615480(196-202)Online publication date: Sep-2018
  • (2017)Twisting Web Pages for Saving EnergyWeb Engineering10.1007/978-3-319-60131-1_13(225-245)Online publication date: 1-Jun-2017
  • (2017)Non-visual Web Browsing: Beyond Web AccessibilityUniversal Access in Human–Computer Interaction. Designing Novel Interactions10.1007/978-3-319-58703-5_24(322-334)Online publication date: 16-May-2017
  • (2016)Reconstructing User’s Attention on the Web through Mouse Movements and Perception-Based Content IdentificationACM Transactions on Applied Perception10.1145/291212413:3(1-21)Online publication date: 28-May-2016
  • (2016)Specification and discovery of web patternsInformation Sciences: an International Journal10.1016/j.ins.2015.08.052328:C(528-545)Online publication date: 20-Jan-2016
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