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Supporting virtual documents in just-in-time hypermedia systems

Published: 28 October 2004 Publication History

Abstract

Many analytical or computational applications especially legacy systems create documents and display screens in response to user queries "dynamically" or in "real time". These "virtual documents" do not exist in advance and thus hypermedia features must be generated "just in time" - automatically and dynamically. Additionally the hypermedia features may have to cause target documents to be generated or re-generated. This paper focuses on the specific challenges faced in hypermedia support for virtual documents of dynamic hypermedia functionality dynamic regeneration and dynamic anchor re-identification and re-location. It presents a prototype called JHE (Just-in-time Hypermedia Engine) to support just-in-time hypermedia across third party applications with dynamic content and discusses issues prompted by this research.

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cover image ACM Conferences
DocEng '04: Proceedings of the 2004 ACM symposium on Document engineering
October 2004
252 pages
ISBN:1581139381
DOI:10.1145/1030397
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: 28 October 2004

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Author Tags

  1. dynamic hypermedia functionality
  2. dynamic regeneration
  3. integration architecture
  4. just-in-time hypermedia
  5. re-identification
  6. re-location
  7. virtual documents

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DocEng04
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DocEng04: ACM Symposium on Document Engineering
October 28 - 30, 2004
Wisconsin, Milwaukee, USA

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Overall Acceptance Rate 194 of 564 submissions, 34%

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