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  1. Proceedings of the 3rd international workshop on Link discovery (LinkKDD '05)
  2. Graph building as a mining activity: finding links in the small
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Bayes net graphs to understand co-authorship networks?
EventRank: a framework for ranking time-varying networks
Graph building as a mining activity: finding links in the small
Tuning representations of dynamic network data
Group and topic discovery from relations and text
The political blogosphere and the 2004 U.S. election: divided they blog
Capital and benefit in social networks
Email alias detection using social network analysis
Mining hidden community in heterogeneous social networks
GiveALink: mining a semantic network of bookmarks for web search and recommendation
Discovering important nodes through graph entropy the case of Enron email database
A latent mixed membership model for relational data
Discovering missing links in Wikipedia

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Graph building as a mining activity: finding links in the small

Content Provider ACM Digital Library
Author Kantardzic, Mehmed Badia, Antonio
Abstract Many analysis of data proceed by building a graph out of the data set and then using social network theory and similar tools on the result. However, there is no theory concerning the construction of the graph itself, even though this is a very important process. In this paper, we attempt to provide a framework in which the graph building process is formalized and studied. We show the parameters (choices) involved in constructing a graph from raw data, and propose some new ways to combine and analyze the data. We also argue the importance of this approach in several domain applications, including criminal/terrorist investigations.
Starting Page 17
Ending Page 24
Page Count 8
File Format PDF
ISBN 1595932151
DOI 10.1145/1134271.1134274
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2005-08-21
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Link analysis Network Graph algorithms
Content Type Text
Resource Type Article
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