Uncertain knowledge association through information gain

Research output: Contribution to report/book/conference proceedingsChapter

Authors

  • Da Ruan
  • Athena Tocatlidou
  • Spiros Kaloudis
  • Nikos Lorentzos

Institutes & Expert groups

Documents & links

Abstract

The problem of entity association is at the core of information mining techniques. In this work we propose an approach that links the similarity of two knowledge entities to the effort required to fuse them in one. This is implemented as an iterative updating process. It unites an evolving initial knowledge entity and a piece of new information, which is repeatedly in-corporated, until a convergence state is reached. The number of updating repetitions can be used as an importance index qualifying the new evi-dence.

Details

Original languageEnglish
Title of host publicationIntelligent Data Mining
Place of PublicationHeidelberg
PublisherSpringer
Pages123-135
Volume1
Edition1
ISBN (Print)978-3-540-26256-5
Publication statusPublished - Aug 2005

Keywords

  • Uncertain knowledge updating, Similarity, Information fusion, Fuzzy sets.

ID: 138269