Skip to main navigation Skip to search Skip to main content

Performance-optimized adaptation of personalized Web fragments

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Current Web users request for individualized and highly-newsworthy information that is immediately delivered by existing Web applications. Therefore, pre-developed, static Web pages which have been regarded as best-practice over years are deprecated to support these demands. Consequently, more sophisticated approaches are needed. One answer to this dilemma is to consider dynamical Web page generation performed on Web Application Servers and being able to respond to individual user requests. The downer for this flexibility is that server-side dynamical Web page generation leads to computation overhead by minimizing response answers. For this, the presented paper will show how to realize performance-optimized individual Web pages. The introduced concept is based on single, cacheable Web fragments.
Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Information and Web-based Application and Services
Number of pages10
Publication statusPublished - Sept 2003

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 16 - Peace, Justice and Strong Institutions
    SDG 16 Peace, Justice and Strong Institutions

Fields of science

  • 102001 Artificial intelligence
  • 102006 Computer supported cooperative work (CSCW)
  • 102010 Database systems
  • 102014 Information design
  • 102015 Information systems
  • 102016 IT security
  • 102028 Knowledge engineering
  • 102019 Machine learning
  • 102022 Software development
  • 102025 Distributed systems
  • 502007 E-commerce
  • 505002 Data protection
  • 506002 E-government
  • 509018 Knowledge management
  • 202007 Computer integrated manufacturing (CIM)
  • 102033 Data mining
  • 102035 Data science

Cite this