Talks and Poster Presentations (with Proceedings-Entry):
D. Schall, S. Dustdar:
"Dynamic Context-Sensitive PageRank for Expertise Mining";
Talk: 2nd International Conference on Social Informatics (SocInfo 2010),
- 2010-10-29; in: "Proceedings of the 2nd International Conference on Social Informatics (SocInfo 2010)",
L. Bolc, M. Makowski, A. Wierzbicki (ed.);
Online tools for collaboration and social platforms have become
omnipresent in Web-based environments. Interests and skills of
people evolve over time depending in performed activities and joint collaborations.
We believe that ranking models for recommending experts
or collaboration partners should not only rely on profiles or skill information
that need to be manually maintained and updated by the user.
In this work we address the problem of expertise mining based on performed
interactions between people. We argue that an expertise mining
algorithm must consider a personīs interest and activity level in a certain
collaboration context. Our approach is based on the PageRank algorithm
enhanced by techniques to incorporate contextual link information. An
approach comprising two steps is presented. First, offline analysis of human
interactions considering tagged interaction links and second composition
of ranking scores based on preferences. We evaluate our approach
using an email interaction network.
Project Head Schahram Dustdar:
Created from the Publication Database of the Vienna University of Technology.