Capturing the user's reading context for tailoring summaries

Cécile Paris*, Stephen Wan

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

The web has become a major source of information to learn about a topic. With the continuous growth of information and its high connectivity, it is hard to follow only the links that are relevant and not to get lost in hyperspace. Our aim is to support people who read documents in a highly connected information space, helping them remain on focus. Our contextually-aware in-browser text summarisation tool, IBES, does this by capturing users' current interests and providing users with contextualised summaries of linked documents, to help them decide whether the link is worth following.

Original languageEnglish
Title of host publicationUser Modeling, Adaptation, and Personalization - 17th International Conference, UMAP 2009 formerly UM and AH, Proceedings
Pages337-342
Number of pages6
Volume5535 LNCS
DOIs
Publication statusPublished - 2009
Event17th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2009 - Trento, Italy
Duration: 22 Jun 200926 Jun 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5535 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other17th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2009
CountryItaly
CityTrento
Period22/06/0926/06/09

Keywords

  • Browsing support tool
  • Tailored summaries
  • User's interest

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