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Center-piece subgraphs: problem definition and fast solutions
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Source International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
Philadelphia, PA, USA
SESSION: Research track papers table of contents
Pages: 404 - 413  
Year of Publication: 2006
ISBN:1-59593-339-5
Authors
Hanghang Tong  Carnegie Mellon University, Pittsburgh, PA
Christos Faloutsos  Carnegie Mellon University, Pittsburgh, PA
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

Given Q nodes in a social network (say, authorship network), how can we find the node/author that is the center-piece, and has direct or indirect connections to all, or most of them? For example, this node could be the common advisor, or someone who started the research area that the Q nodes belong to. Isomorphic scenarios appear in law enforcement (find the master-mind criminal, connected to all current suspects), gene regulatory networks (find the protein that participates in pathways with all or most of the given Q proteins), viral marketing and many more.Connection subgraphs is an important first step, handling the case of Q=2 query nodes. Then, the connection subgraph algorithm finds the b intermediate nodes, that provide a good connection between the two original query nodes.Here we generalize the challenge in multiple dimensions: First, we allow more than two query nodes. Second, we allow a whole family of queries, ranging from 'OR' to 'AND', with 'softAND' in-between. Finally, we design and compare a fast approximation, and study the quality/speed trade-off.We also present experiments on the DBLP dataset. The experiments confirm that our proposed method naturally deals with multi-source queries and that the resulting subgraphs agree with our intuition. Wall-clock timing results on the DBLP dataset show that our proposed approximation achieve good accuracy for about 6:1 speedup.


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
B. Aditya, G. Bhalotia, S. Chakrabarti, A. Hulgeri, C. Nakhe, and S. S. Parag. Banks: Browsing and keyword searching in relational databases. In VLDB, pages 1083--1086, 2002.
 
2
R. Albert, H. Jeong, and A.-L. Barabasi. Diameter of the world wide web. Nature, (401):130--131, 1999.
 
3
A. Balmin, V. Hristidis, and Y. Papakonstantinou. Objectrank: Authority-based keyword search in databases. In VLDB, pages 564--575, 2004.
4
 
5
S. Dorogovtsev and J. Mendes. Evolution of networks. Advances in Physics, 51:1079--1187, 2002.
6
 
7
M. Faloutsos, P. Faloutsos, and C. Faloutsos. On power-law relationships of the internet topology. SIGCOMM, pages 251--262, Aug-Sept. 1999.
8
 
9
 
10
F. Geerts, H. Mannila, and E. Terzi. Relational link-based ranking. In VLDB, pages 552--563, 2004.
11
 
12
M. Girvan and M. E. J. Newman. Community structure is social and biological networks.
 
13
M. Grötschel, C. L. Monma, and M. Stoer. Design of survivable networks. In Handbooks in Operations Research and Management Science 7: Network Models. North Holland, 1993.
14
15
16
 
17
18
19
 
20
M. E. J. Newman. The structure and function of complex networks. SIAM Review, 45:167--256, 2003.
 
21
A. Ng, M. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS, pages 849--856, 2001.
 
22
L. Page, S. Brin, R. Motwani, and T. Winograd. The PageRank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998. Paper SIDL-WP-1999-0120 (version of 11/11/1999).
 
23
C. R. Palmer and C. Faloutsos. Electricity based external similarity of categorical attributes. PAKDD 2003, April-May 2003.
24
25
 
26
 
27
 
28
D. Zhou, O. Bousquet, T. Lal, J. Weston, and B. Scholkopf. Learning with local and global consistency. In NIPS, 2003.

CITED BY  9

Collaborative Colleagues:
Hanghang Tong: colleagues
Christos Faloutsos: colleagues