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iLink: search and routing in social networks
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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
San Jose, California, USA
SESSION: Industrial and government track papers table of contents
Pages: 931 - 940  
Year of Publication: 2007
ISBN:978-1-59593-609-7
Authors
Jeffrey Davitz  SRI International, Menlo Park, CA
Jiye Yu  SRI International, Menlo Park, CA
Sugato Basu  Google Research, Mountain View, CA
David Gutelius  SRI International, Menlo Park, CA
Alexandra Harris  SRI International, Menlo Park, CA
Sponsors
ACM: Association for Computing Machinery
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

The growth of Web 2.0 and fundamental theoretical breakthroughs have led to an avalanche of interest in social networks. This paper focuses on the problem of modeling how social networks accomplish tasks through peer production style collaboration. We propose a general interaction model for the underlying social networks and then a specific model (iLink for social search and message routing. A key contribution here is the development of a general learning framework for making such online peer production systems work at scale. The iLink model has been used to develop a system for FAQ generation in a social network (FAQtory), and experience with its application in the context of a full-scale learning-driven workflow application (CALO) is reported. We also discuss methods of adapting iLink technology for use in military knowledge sharing portals and other message routing systems. Finally, the paper shows the connection of iLink to SQM, a theoretical model for social search that is a generalization of Markov Decision Processes and the popular Pagerank model.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
L. A. Adamic and E. Adar. How to search a social network. Social Networks, 27(3):187--203, July 2005.
 
2
A. Banerjee and S. Basu. A social query model for decentralized search. Technical report, University of Minnesota, 2007.
 
3
A. Banerjee and S. Basu. Topic models over text streams: A study of batch and online unsupervised learning. In Proc. of the 7th SIAM Intl. Conf. on Data Mining, 2007.
 
4
A. Banerjee, S. Basu, and S. Merugu. Multiway clustering on relation graphs. In Proc. of the 7th SIAM Intl. Conf. on Data Mining, 2007.
5
 
6
G. W. Beck and V. Wieland. Learning and control in a changing economic environment. Journal of Economic Dynamics and Control, 26(9-10):1359--1377, August 2002.
 
7
R. Bellman. A Markovian decision process. Journal of Mathematics and Mechanics 6, pages 679--684, 1957.
 
8
Y. Benkler. Coase's penguin, or Linux and the nature of the firm. Yale Law Journal, 112, 2002.
 
9
Y. Benkler. The Wealth of Networks. Yale University Press, 2006.
 
10
L. Y.-K. Blanc, A. and A. Vahdat. Designing incentives for peer-to-peer routing. In 2nd wokshop on Economics of peer-to-peer Systems, 2004.
 
11
 
12
R. Cross, A. Parker, L. Prusak, and S. Borgatti. Knowing what we know: Supporting knowledge creation and sharing in social networks. Organizational Dynamics, 302(2):100--120, 2001.
13
 
14
 
15
R. A. Ghosh. Cooking pot markets: An economic model for the trade in free goods and services on the internet. First Monday, 3(3), 1998.
16
 
17
S. M. Kakade, M. Kearns, L. E. Ortiz, R. Pemantle, and S. Suri. Economic properties of social networks. In Advances in Neural Info. Processing Systems 17, 2005.
18
19
 
20
 
21
J. Lerner and J. Tirole. Some simple economics of open source. Journal of Industrial Economics, 50(2):197--234, 2002.
22
 
23
D. Liben-Nowell, J. Novak, R. Kumar, P. Raghavan, and A. Tomkins. Geographic routing in social networks. Proc. National Academy of Sciences, 102(33), 2005.
 
24
A. McCallum, A. Corrada-Emmanuel, and X. Wang. Topic and role discovery in social networks. In Proc. of Intl. Joint Conf. on AI, 2005.
 
25
 
26
M. E. J. Newman. The structure and function of complex networks. SIAM Review, 45:167--256, 2003.
 
27
R. Pemantle and B. Skyrms. A dynamic model of social network formation. Proc. of the National Academy of Sciences, 2000.
 
28
29
 
30
31
 
32
 
33
D. Watts and S. Strogatz. Collective dynamics of 'small-world' networks. Nature, 393(6684):440--442, 1998.
 
34
D. J. Watts, P. S. Dodds, and M. E. J. Newman. Identity and search in social networks. Science, 296:1302--1305, 2002.
 
35
F. Wu, B. A. Huberman, L. A. Adamic, and J. R. Tyler. Information flow in social groups. Physica A, 337:327--335,2004.

Collaborative Colleagues:
Jeffrey Davitz: colleagues
Jiye Yu: colleagues
Sugato Basu: colleagues
David Gutelius: colleagues
Alexandra Harris: colleagues