Capturing knowledge worker behavior based on information diffusion theory

Masayuki Ishikawa, Peter Geczy, Noriaki Izumi, Takahira Yamaguchi

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

Abstract

By analyzing the information diffusion in a studied large scale corporate portal, we discovered that only small population of users is sufficient to initiate the widespread of innovation. Applying these findings, we conducted analytic experiment for novel recommendation algorithm based on the browsing features of identified selected users and discovered that the first 10 users accessing a particular page play the key role in the information spread.

Original languageEnglish
Title of host publicationKnowledge-Based Software Engineering. Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering
PublisherIOS Press
Pages378-382
Number of pages5
Edition1
ISBN (Print)9781586039004
DOIs
Publication statusPublished - 2008 Jan 1

Publication series

NameFrontiers in Artificial Intelligence and Applications
Number1
Volume180
ISSN (Print)0922-6389

Keywords

  • Collaborative filtering
  • Information Diffusion
  • Innovator theory
  • Knowledge management technology
  • Recommender System

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Ishikawa, M., Geczy, P., Izumi, N., & Yamaguchi, T. (2008). Capturing knowledge worker behavior based on information diffusion theory. In Knowledge-Based Software Engineering. Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (1 ed., pp. 378-382). (Frontiers in Artificial Intelligence and Applications; Vol. 180, No. 1). IOS Press. https://doi.org/10.3233/978-1-58603-900-4-378