Dynamic models of expert groups to recommend web documents

Dae Eun Kim, Sea Woo Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Recently most recommender systems have been developed to recommend items or documents based on user preferences for a particular user, but they have difficulty in deriving user preferences for users who have not rated many documents. In this paper we use dynamic expert groups which are automatically formed to recommend domainspecific documents for unspecified users. The group members have dynamic authority weights depending on their performance of the ranking evaluations. Human evaluations over web pages are very effective to find relevant information in a specific domain. In addition, we have tested several effectiveness measures on rank order to determine if the current top-ranked lists recommended by experts are reliable. We show simulation results to check the possibility of dynamic expert group models for recommender systems.

Original languageEnglish
Title of host publicationResearch and Advanced Technology for Digital Libraries - 5th European Conference, ECDL 2001, Proceedings
EditorsPanos Constantopoulos, Panos Constantopoulos, Ingeborg T. Sølvberg
PublisherSpringer Verlag
Number of pages12
ISBN (Electronic)9783540425373
Publication statusPublished - 2001
Event5th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2001 - Darmstadt, Germany
Duration: 2001 Sept 42001 Sept 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th European Conference on Research and Advanced Technology for Digital Libraries, ECDL 2001

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2001.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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