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How to Find Important Users in a Web Community? Mining Similarity Graphs

Authors:
Clemens Schefels

Keywords: Web, User Profiles, Explicit Feedback, Implicit Feedback, Graphs, Similarity Graph, Graph mining, Mining, Network, Social Network, Web 2.0, Computer aided analysis, World Wide Web, Data analysis, Graph theory

Abstract:
In this paper we provide a useful tool to the web site owner for enhancing her/his marketing strategies and rise as consequence the click rates on her/his web site. Our approach addresses the following research questions: which users are important for the web community? Which users have similar interests? How similar are the interests of the users of the web community? How is this specific community structured? We present a framework for building and analyzing weighted similarity graphs, e.g., for a social web community. For that, we provide measurements for user equality and user similarity. Furthermore, we introduce different graph types for analyzing profiles of web community users. We present two new algorithms for finding important users of a community.

Pages: 10 to 17

Copyright: Copyright (c) IARIA, 2012

Publication date: September 23, 2012

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-242-4

Location: Barcelona, Spain

Dates: from September 23, 2012 to September 28, 2012