umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Web prefetching through automatic categorization
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
2004 (English)Report (Other academic)
Abstract [en]

The present report provides a novel transparent and speculative algorithm for content based web page prefetching. The proposed algorithm relies on a user profile that is dynamically generated when the user is browsing the Internet and is updated over time. The objective is to reduce the user perceived latency by anticipating future actions. In doing so the adaboost algorithm is used in order to automatically annotate the outbound links of a page to a predefined set of “labels”. Afterwards, the links that correspond to labels relevant to the user’s preferences are pre-fetched in an effort to reduce the perceived latency when the user is surfing the Internet. A comparison between the proposed algorithm against two other pre-fetching algorithms yield improved cache-hit rates given a moderate bandwidth overhead.

Place, publisher, year, edition, pages
Umeå: Tillämpad fysik och elektronik , 2004. , 14 p.
Series
DML Technical Report, ISSN 1652-8441 ; DML-TR-2004:04
Keyword [en]
Signalbehandling, Link pre-fetching, adaboosting, user behavior modeling
Keyword [sv]
Signalbehandling
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:umu:diva-409OAI: oai:DiVA.org:umu-409DiVA: diva2:143389
Available from: 2004-12-22 Created: 2004-12-22 Last updated: 2016-02-23Bibliographically approved

Open Access in DiVA

fulltext(275 kB)356 downloads
File information
File name FULLTEXT01.pdfFile size 275 kBChecksum MD5
4d76147530ccec35f78fa58e8890606177423a42af629bc55ac0451c066fe47236f0e150
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Li, Haibo
By organisation
Department of Applied Physics and Electronics
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 356 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 260 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf