Modelling semantic relationships and centrality to facilitate community knowledge sharing

Styliani Kleanthous, Vania Dimitrova

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

10 Citations (Scopus)

Abstract

Some of today's most widely spread applications are social systems where people can form communities and share knowledge. However, knowledge sharing is not always effective and communities often do not sustain. Can user modelling approaches help to identify what support could be offered and how this would benefit the community? The paper presents algorithms for extracting a model of a closely-knit virtual community following processes identified as important for effective communities. The algorithms are applied to get an insight of a real virtual community and to identify what support may be needed to help the community function better as an entity.

Original languageEnglish
Title of host publicationAdaptive Hypermedia and Adaptive Web-Based Systems - 5th International Conference, AH 2008, Proceedings
Pages123-132
Number of pages10
Volume5149 LNCS
DOIs
Publication statusPublished - 2008
Event5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2008 - Hannover, Germany
Duration: 29 Jul 20081 Aug 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5149 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 2008
CountryGermany
CityHannover
Period29/07/081/08/08

Keywords

  • Community Adaptation
  • Community Model
  • Knowledge Sharing

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    Kleanthous, S., & Dimitrova, V. (2008). Modelling semantic relationships and centrality to facilitate community knowledge sharing. In Adaptive Hypermedia and Adaptive Web-Based Systems - 5th International Conference, AH 2008, Proceedings (Vol. 5149 LNCS, pp. 123-132). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5149 LNCS). https://doi.org/10.1007/978-3-540-70987-9_15