-
1
-
-
0027621699
-
Mining association rules between sets of items in large databases
-
R. Agrawal, T. Imielinski, and A. N. Swami. Mining association rules between sets of items in large databases. In SIGMOD, pp. 207-216, 1993.
-
(1993)
SIGMOD
, pp. 207-216
-
-
Agrawal, R.1
Imielinski, T.2
Swami, A.N.3
-
2
-
-
84980104458
-
Financial ratios, discriminant analysis and the prediction of corporate bankruptcy
-
E. I. Altman. Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4):589-609, 1968.
-
(1968)
The Journal of Finance
, vol.23
, Issue.4
, pp. 589-609
-
-
Altman, E.I.1
-
3
-
-
12244300524
-
A probabilistic framework for semi-supervised clustering
-
S. Basu, M. Bilenko, and R. J. Mooney. A probabilistic framework for semi-supervised clustering. In KDD, pp. 59-68, 2004.
-
(2004)
KDD
, pp. 59-68
-
-
Basu, S.1
Bilenko, M.2
Mooney, R.J.3
-
4
-
-
84880088253
-
-
CEURWS.org
-
R. J. Bayardo, B. Goethals, and M. J. Zaki, editors. FIMI '04, Proceedings of the IEEE ICDM Workshop on Frequent Item-set Mining Implementations, Volume 126 of CEUR Workshop Proceedings. CEURWS.org, 2004.
-
(2004)
FIMI '04, Proceedings of the IEEE ICDM Workshop on Frequent Item-set Mining Implementations, Volume 126 of CEUR Workshop Proceedings
-
-
Bayardo, R.J.1
Goethals, B.2
Zaki, M.J.3
-
5
-
-
84947205653
-
When is "nearest neighbor," meaningful?
-
K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is "nearest neighbor," meaningful? In ICDT, pp. 217-235, 1999.
-
(1999)
ICDT
, pp. 217-235
-
-
Beyer, K.S.1
Goldstein, J.2
Ramakrishnan, R.3
Shaft, U.4
-
7
-
-
84924933542
-
Valuation ratios and the long run stock market outlook: An update
-
Princeton University Press
-
J. Y. Campbell and R. J. Shiller. Valuation ratios and the long run stock market outlook: An update. In Advances in Behavioral Finance II. Princeton University Press, 2005.
-
(2005)
Advances in Behavioral Finance II
-
-
Campbell, J.Y.1
Shiller, R.J.2
-
8
-
-
52649098497
-
Data peeler: Contraint-based closed pattern mining in n-ary relations
-
L. Cerf, J. Besson, C. Robardet, and J.-F. Boulicaut. Data peeler: Contraint-based closed pattern mining in n-ary relations. In SDM, pp. 37-48, 2008.
-
(2008)
SDM
, pp. 37-48
-
-
Cerf, L.1
Besson, J.2
Robardet, C.3
Boulicaut, J.-F.4
-
9
-
-
77952760641
-
Constrained locally weighted clustering
-
H. Cheng, K. A. Hua, and K. Vu. Constrained locally weighted clustering. PVLDB, 1(1):90-101, 2008.
-
(2008)
PVLDB
, vol.1
, Issue.1
, pp. 90-101
-
-
Cheng, H.1
Hua, K.A.2
Vu, K.3
-
10
-
-
0034566393
-
Biclustering of expression data
-
Y. Cheng and G. M. Church. Biclustering of expression data. In ISMB, pp. 93-103, 2000.
-
(2000)
ISMB
, pp. 93-103
-
-
Cheng, Y.1
Church, G.M.2
-
11
-
-
84880122180
-
-
[Last accessed 2009]
-
Compustat. http://www.compustat.com [Last accessed 2009].
-
-
-
-
15
-
-
65449186692
-
Quantitative evaluation of approximate frequent pattern mining algorithms
-
R. Gupta, G. Fang, B. Field, M. Steinbach, and V. Kumar. Quantitative evaluation of approximate frequent pattern mining algorithms. In KDD, pp. 301-309, 2008.
-
(2008)
KDD
, pp. 301-309
-
-
Gupta, R.1
Fang, G.2
Field, B.3
Steinbach, M.4
Kumar, V.5
-
16
-
-
84880104543
-
-
[Last accessed 2009]
-
Investopedia. http://www.investopedia.com/university/ratios/ [Last accessed 2009].
-
-
-
-
17
-
-
78149244925
-
Mining frequent closed cubes in 3D datasets
-
L. Ji, K.-L. Tan, and A. K. H. Tung. Mining frequent closed cubes in 3D datasets. In VLDB, pp. 811-822, 2006.
-
(2006)
VLDB
, pp. 811-822
-
-
Ji, L.1
Tan, K.-L.2
Tung, A.K.H.3
-
19
-
-
27144558697
-
A microe-conomic view of data mining
-
J. Kleinberg, C. Papadimitriou, and P. Raghavan. A microe-conomic view of data mining. Data Mining and Knowledge Discovery, 2(4):311-324, 1998.
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, Issue.4
, pp. 311-324
-
-
Kleinberg, J.1
Papadimitriou, C.2
Raghavan, P.3
-
20
-
-
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. ACM Transactions on Knowledge Discovery from Data, 3(1):1-58, 2009.
-
(2009)
ACM Transactions on Knowledge Discovery from Data
, vol.3
, Issue.1
, pp. 1-58
-
-
Kriegel, H.-P.1
Kröger, P.2
Zimek, A.3
-
21
-
-
79951742996
-
Density-connected subspace clustering for high-dimensional data
-
P. Kröger, H.-P. Kriegel, and K. Kailing. Density-connected subspace clustering for high-dimensional data. In SDM, pp. 246-257, 2004.
-
(2004)
SDM
, pp. 246-257
-
-
Kröger, P.1
Kriegel, H.-P.2
Kailing, K.3
-
22
-
-
7444239079
-
Predicting returns with financial ratios
-
J. W. Lewellen. Predicting returns with financial ratios. Journal of Financial Economics, 74:209-235, 2004.
-
(2004)
Journal of Financial Economics
, vol.74
, pp. 209-235
-
-
Lewellen, J.W.1
-
23
-
-
34548723854
-
Distance based subspace clustering with flexible dimension partitioning
-
G. Liu, J. Li, K. Sim, and L. Wong. Distance based subspace clustering with flexible dimension partitioning. In ICDE, pp. 1250-1254, 2007.
-
(2007)
ICDE
, pp. 1250-1254
-
-
Liu, G.1
Li, J.2
Sim, K.3
Wong, L.4
-
24
-
-
65449163900
-
Finding non-redundant, statistically significant regions in high dimensional data: A novel approach to projected and subspace clustering
-
G. Moise and J. Sander. Finding non-redundant, statistically significant regions in high dimensional data: a novel approach to projected and subspace clustering. In KDD, pp. 533-541, 2008.
-
(2008)
KDD
, pp. 533-541
-
-
Moise, G.1
Sander, J.2
-
25
-
-
0000672424
-
Fast learning in networks of locally-tuned processing units
-
J. Moody and C. J. Darken. Fast learning in networks of locally-tuned processing units. Neural Computation, 1(2):281-294, 1989.
-
(1989)
Neural Computation
, vol.1
, Issue.2
, pp. 281-294
-
-
Moody, J.1
Darken, C.J.2
-
27
-
-
79951764492
-
A test of ben graham's stock selection criteria
-
H. R. Oppenheimer. A test of ben graham's stock selection criteria. Financial Analysts Journal, 40(5):68-74, 1984.
-
(1984)
Financial Analysts Journal
, vol.40
, Issue.5
, pp. 68-74
-
-
Oppenheimer, H.R.1
-
28
-
-
55049091309
-
LCM ver. 2: Efficient mining algorithms for frequent/closed/maximal itemsets
-
T. Uno, M. Kiyomi, and H. Arimura. LCM ver. 2: Efficient mining algorithms for frequent/closed/maximal itemsets. In FIMI, 2004.
-
(2004)
FIMI
-
-
Uno, T.1
Kiyomi, M.2
Arimura, H.3
-
29
-
-
84880092484
-
-
U.S. Securities and Exchange Commission [Last accessed 2009]
-
U.S. Securities and Exchange Commission. Microcap stock: A guide for investors. http://www.sec.gov/investor/pubs/microcapstock.htm [Last accessed 2009].
-
Microcap Stock: A Guide for Investors
-
-
-
30
-
-
84883810104
-
Profit mining: From patterns to actions
-
K. Wang, S. Zhou, and J. Han. Profit mining: From patterns to actions. In EDBT, pp. 70-87, 2002.
-
(2002)
EDBT
, pp. 70-87
-
-
Wang, K.1
Zhou, S.2
Han, J.3
-
31
-
-
23944511670
-
Mining customer value: From association rules to direct marketing
-
K. Wang, S. Zhou, Q. Yang, and J. M. S. Yeung. Mining customer value: From association rules to direct marketing. Data Mining and Knowledge Discovery, 11(1):57-79, 2005.
-
(2005)
Data Mining and Knowledge Discovery
, vol.11
, Issue.1
, pp. 57-79
-
-
Wang, K.1
Zhou, S.2
Yang, Q.3
Yeung, J.M.S.4
-
32
-
-
67649659857
-
Finding time-lagged 3D clusters
-
X. Xu, Y. Lu, K.-L. Tan, and A. K. H. Tung. Finding time-lagged 3D clusters. In ICDE, pp. 445-456, 2009.
-
(2009)
ICDE
, pp. 445-456
-
-
Xu, X.1
Lu, Y.2
Tan, K.-L.3
Tung, A.K.H.4
-
33
-
-
28444491389
-
On discovery of extremely low-dimensional clusters using semi-supervised projected clustering
-
K. Y. Yip, D. W. Cheung, and M. K. Ng. On discovery of extremely low-dimensional clusters using semi-supervised projected clustering. In ICDE, pp. 329-340, 2005.
-
(2005)
ICDE
, pp. 329-340
-
-
Yip, K.Y.1
Cheung, D.W.2
Ng, M.K.3
-
34
-
-
29844442223
-
TRICLUSTER: An effective algorithm for mining coherent clusters in 3D microarray data
-
L. Zhao and M. J. Zaki. TRICLUSTER: an effective algorithm for mining coherent clusters in 3D microarray data. In SIGMOD, pp. 694-705, 2005.
-
(2005)
SIGMOD
, pp. 694-705
-
-
Zhao, L.1
Zaki, M.J.2
|