-
2
-
-
84947205653
-
When is "nearest neighbor" meaningful?
-
K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is "nearest neighbor" meaningful? In ICDT, pages 217-235, 1999.
-
(1999)
ICDT
, pp. 217-235
-
-
Beyer, K.S.1
Goldstein, J.2
Ramakrishnan, R.3
Shaft, U.4
-
3
-
-
70349884040
-
Discovering relevant cross-graph cliques in dynamic networks
-
L. Cerf, T. B. N. Nguyen, and J.-F. Boulicaut. Discovering relevant cross-graph cliques in dynamic networks. In ISMIS, pages 513-522, 2009.
-
(2009)
ISMIS
, pp. 513-522
-
-
Cerf, L.1
Nguyen, T.B.N.2
Boulicaut, J.-F.3
-
4
-
-
74049087026
-
Community detection in graphs
-
S. Fortunato. Community detection in graphs. Physics Reports, 486(3-5):75-174, 2010.
-
(2010)
Physics Reports
, vol.486
, Issue.3-5
, pp. 75-174
-
-
Fortunato, S.1
-
5
-
-
83055191163
-
External evaluation measures for subspace clustering
-
S. Günnemann, I. Färber, E. Müller, I. Assent, and T. Seidl. External evaluation measures for subspace clustering. In CIKM, pages 1363-1372, 2011.
-
(2011)
CIKM
, pp. 1363-1372
-
-
Günnemann, S.1
Färber, I.2
Müller, E.3
Assent, I.4
Seidl, T.5
-
6
-
-
80052417297
-
DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors
-
S. Günnemann, B. Boden, and T. Seidl. DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors. In ECML/PKDD (1), pages 565-580, 2011.
-
(2011)
ECML/PKDD
, Issue.1
, pp. 565-580
-
-
Günnemann, S.1
Boden, B.2
Seidl, T.3
-
7
-
-
79951736796
-
Subspace clustering meets dense subgraph mining: A synthesis of two paradigms
-
S. Günnemann, I. Färber, B. Boden, and T. Seidl. Subspace clustering meets dense subgraph mining: A synthesis of two paradigms. In ICDM, pages 845-850, 2010.
-
(2010)
ICDM
, pp. 845-850
-
-
Günnemann, S.1
Färber, I.2
Boden, B.3
Seidl, T.4
-
9
-
-
84899829959
-
A formal basis for the heuristic determination of minimum cost paths
-
P. Hart, N. Nilsson, and B. Raphael. A formal basis for the heuristic determination of minimum cost paths. Systems Science and Cybernetics, 4(2):100-107, 1968.
-
(1968)
Systems Science and Cybernetics
, vol.4
, Issue.2
, pp. 100-107
-
-
Hart, P.1
Nilsson, N.2
Raphael, B.3
-
10
-
-
67149084291
-
Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering
-
H.-P. Kriegel, P. Kröger, and A. Zimek. Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering. TKDD, 3(1):1-58, 2009.
-
(2009)
TKDD
, vol.3
, Issue.1
, pp. 1-58
-
-
Kriegel, H.-P.1
Kröger, P.2
Zimek, A.3
-
11
-
-
14844298776
-
Weighted networks of scientific communication: The measurement and topological role of weight
-
M. Li, Y. Fan, J. Chen, L. Gao, Z. Di, and J. Wu. Weighted networks of scientific communication: the measurement and topological role of weight. Physica A: Statistical Mechanics and its Applications, 350(2):643-656, 2005.
-
(2005)
Physica A: Statistical Mechanics and Its Applications
, vol.350
, Issue.2
, pp. 643-656
-
-
Li, M.1
Fan, Y.2
Chen, J.3
Gao, L.4
Di, Z.5
Wu, J.6
-
12
-
-
56049105454
-
Effective pruning techniques for mining quasi-cliques
-
G. Liu and L. Wong. Effective pruning techniques for mining quasi-cliques. In ECML/PKDD (2), pages 33-49, 2008.
-
(2008)
ECML/PKDD
, Issue.2
, pp. 33-49
-
-
Liu, G.1
Wong, L.2
-
13
-
-
77951149821
-
Relevant subspace clustering: Mining the most interesting non-redundant concepts in high dimensional data
-
E. Müller, I. Assent, S. Günnemann, R. Krieger, and T. Seidl. Relevant subspace clustering: Mining the most interesting non-redundant concepts in high dimensional data. In ICDM, pages 377-386, 2009.
-
(2009)
ICDM
, pp. 377-386
-
-
Müller, E.1
Assent, I.2
Günnemann, S.3
Krieger, R.4
Seidl, T.5
-
14
-
-
74549169516
-
Mining cohesive patterns from graphs with feature vectors
-
F. Moser, R. Colak, A. Rafiey, and M. Ester. Mining cohesive patterns from graphs with feature vectors. In SDM, pages 593-604, 2009.
-
(2009)
SDM
, pp. 593-604
-
-
Moser, F.1
Colak, R.2
Rafiey, A.3
Ester, M.4
-
15
-
-
84865086248
-
Evaluating clustering in subspace projections of high dimensional data
-
E. Müller, S. Günnemann, I. Assent, and T. Seidl. Evaluating clustering in subspace projections of high dimensional data. In VLDB, pages 1270-1281, 2009.
-
(2009)
VLDB
, pp. 1270-1281
-
-
Müller, E.1
Günnemann, S.2
Assent, I.3
Seidl, T.4
-
17
-
-
32344444324
-
On mining cross-graph quasi-cliques
-
J. Pei, D. Jiang, and A. Zhang. On mining cross-graph quasi-cliques. In SIGKDD, pages 228-238, 2005.
-
(2005)
SIGKDD
, pp. 228-238
-
-
Pei, J.1
Jiang, D.2
Zhang, A.3
-
18
-
-
0039074502
-
Search through systematic set enumeration
-
R. Rymon. Search through systematic set enumeration. In KR, pages 539-550, 1992.
-
(1992)
KR
, pp. 539-550
-
-
Rymon, R.1
-
19
-
-
36849029834
-
A spectral clustering approach to optimally combining numerical vectors with a modular network
-
M. Shiga, I. Takigawa, and H. Mamitsuka. A spectral clustering approach to optimally combining numerical vectors with a modular network. In SIGKDD, pages 647-656, 2007.
-
(2007)
SIGKDD
, pp. 647-656
-
-
Shiga, M.1
Takigawa, I.2
Mamitsuka, H.3
-
20
-
-
33749600907
-
Clan: An algorithm for mining closed cliques from large dense graph databases
-
J. Wang, Z. Zeng, and L. Zhou. Clan: An algorithm for mining closed cliques from large dense graph databases. In ICDE, page 73, 2006.
-
(2006)
ICDE
, pp. 73
-
-
Wang, J.1
Zeng, Z.2
Zhou, L.3
-
21
-
-
33749560883
-
Coherent closed quasi-clique discovery from large dense graph databases
-
Z. Zeng, J. Wang, L. Zhou, and G. Karypis. Coherent closed quasi-clique discovery from large dense graph databases. In SIGKDD, pages 797-802, 2006.
-
(2006)
SIGKDD
, pp. 797-802
-
-
Zeng, Z.1
Wang, J.2
Zhou, L.3
Karypis, G.4
|