J. Han and M. Kamber, Data Mining, 2000.
DOI : 10.1007/978-1-4899-7993-3_104-2

G. Piatetsky-shapiro and C. J. Matheus, The interingness of deviations, Proc. KDD Workshop, pp.25-36, 1994.

M. Klemettinen, H. Mannila, and H. Toivonen, A data mining methodology and its application to semi-automatic knowledge acquisition, Database and Expert Systems Applications. 8th International Conference, DEXA '97. Proceedings, pp.670-677, 1997.
DOI : 10.1109/DEXA.1997.617410

A. Choudhary, J. Harding, and M. Tiwari, Data mining in manufacturing: a review based on the kind of knowledge, Journal of Intelligent Manufacturing, vol.24, issue.3, pp.501-521, 2009.
DOI : 10.1007/s10845-008-0145-x

J. Pan and D. Tai, Implementing virtual metrology for in-line quality control in semiconductor manufacturing, International Journal of Systems Science, vol.19, issue.5, pp.461-470, 2009.
DOI : 10.1109/TSM.2007.907609

L. Huisman, Data Mining and Diagnosing IC Fails, 2005.

M. A. Karim, S. K. Halgamuge, A. J. Smith, and A. L. Hsu, Manufacturing Yield Improvement by Clustering, Proc. ICONIP, pp.526-534, 2006.
DOI : 10.1007/11893295_58

D. Braha and A. Shmilovici, Data mining for improving a cleaning process in the semiconductor industry, IEEE Transactions on Semiconductor Manufacturing, vol.15, issue.1, pp.91-101, 2002.
DOI : 10.1109/66.983448

D. Braha and A. Shmilovici, On the use of decision tree induction for discovery of interactions in a photolithographic process, IEEE Transactions on Semiconductor Manufacturing, vol.16, issue.4, pp.644-652, 2003.
DOI : 10.1109/TSM.2003.818959

D. Baek, I. Jeong, and C. H. Han, Application of Data Mining for Improving Yield in Wafer Fabrication System, Proc. ICCSA,v o l .4, pp.222-231, 2005.
DOI : 10.1007/11424925_25

D. Mackay-cambridge and U. K. , An Example Inference Task: Clustering, pp.284-292, 2003.

C. Chien, W. Wang, and J. Cheng, Data mining for yield enhancement in semiconductor manufacturing and an empirical study, Expert Systems with Applications, vol.33, issue.1, pp.192-198, 2007.
DOI : 10.1016/j.eswa.2006.04.014

L. Rokach and O. Maimon, Data Mining for Improving the Quality of Manufacturing: A Feature Set Decomposition Approach, Journal of Intelligent Manufacturing, vol.19, issue.7, pp.285-299, 2006.
DOI : 10.1007/s10845-005-0005-x

C. Huang and R. Chen, Application of new a priori algorithm MDNC to TFT-LCD array manufacturing yield improvement

W. Chen, S. Tseng, and C. Wang, A novel manufacturing defect detection method using association rule mining techniques, Expert Systems with Applications, vol.29, issue.4, pp.807-815, 2005.
DOI : 10.1016/j.eswa.2005.06.004

H. Sadoyan, A. Zakarian, and P. Mohanty, Data mining algorithm for manufacturing process control, The International Journal of Advanced Manufacturing Technology, vol.28, issue.3-4, pp.3-4, 2006.
DOI : 10.1007/s00170-004-2367-1

URL : http://deepblue.lib.umich.edu/bitstream/2027.42/45889/1/170_2004_Article_2367.pdf

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1999.

S. Brin, R. Motwani, and C. Silverstein, Beyond market baskets: Generalizing association rules to correlations, Proc. SIGMOD Conf, pp.265-276, 1997.

M. Laporte, N. Novelli, R. Cicchetti, and L. Lakhal, Computing Full and Iceberg Datacubes Using Partitions, Proc. ISMIS, pp.244-254, 2002.
DOI : 10.1007/3-540-48050-1_28

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.468.7208

R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo, Fast discovery of association rules, Advances in Knowledge Discovery and Data Mining, pp.307-328, 1996.

X. Wu, C. Zhang, and S. Zhang, Efficient mining of both positive and negative association rules, ACM Transactions on Information Systems, vol.22, issue.3, pp.381-405, 2004.
DOI : 10.1145/1010614.1010616

G. Grahne, L. V. Lakshmanan, and X. Wang, Efficient mining of constrained correlated sets, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), pp.512-521, 2000.
DOI : 10.1109/ICDE.2000.839450

M. Vel, Theory of Convex Structures, 1993.

H. Hirsh, Generalizing version spaces, Machine Learning, vol.2, issue.1, pp.5-46, 1994.
DOI : 10.1007/BF00993863

M. Spiegel and L. Stephens, Outline of Statistics, 1998.

D. Moore, Measures of lack of fit from tests of chi-squared type, Proc. EGC, pp.151-166, 1984.
DOI : 10.1016/0378-3758(84)90067-3

D. Laurent and N. Spyratos, Partition semantics for incomplete information in relational databases, Proc. SIGMOD Conf, pp.66-73, 1988.

H. Mannila and H. Toivonen, Levelwise search and borders of theories in knowledge discovery, Data Mining and Knowledge Discovery, vol.1, issue.3, pp.241-258, 1997.
DOI : 10.1023/A:1009796218281

F. Flouvat, F. D. Marchi, and J. Petit, A Thorough Experimental Study of Datasets for Frequent Itemsets, Fifth IEEE International Conference on Data Mining (ICDM'05), pp.162-169, 2005.
DOI : 10.1109/ICDM.2005.15

D. Pyle, Data Preparation for Data Mining, 1999.

O. Stepankova, P. Aubrecht, Z. Kouba, and P. Miksovsky, Preprocessing for data mining and decision support, " in Data Mining and Decision Support: Integration and Collaboration The Netherlands, pp.107-117, 2003.

H. Liu, F. Hussain, C. L. Tan, and M. Dash, Discretization: An enabling technique, Data Mining and Knowledge Discovery, vol.6, issue.4, pp.393-423, 2002.
DOI : 10.1023/A:1016304305535

G. Jenks, The data model concept in statistical mapping, International Yearbook of Cartography, pp.186-190, 1967.

W. Fisher, On Grouping for Maximum Homogeneity, Journal of the American Statistical Association, vol.40, issue.284, pp.789-798, 1958.
DOI : 10.2307/1907923

J. Han and M. Kamber, Data Mining, 2000.
DOI : 10.1007/978-1-4899-7993-3_104-2

G. Piatetsky-shapiro and C. J. Matheus, The interingness of deviations, Proc. KDD Workshop, pp.25-36, 1994.

M. Klemettinen, H. Mannila, and H. Toivonen, A data mining methodology and its application to semi-automatic knowledge acquisition, Database and Expert Systems Applications. 8th International Conference, DEXA '97. Proceedings, pp.670-677, 1997.
DOI : 10.1109/DEXA.1997.617410

A. Choudhary, J. Harding, and M. Tiwari, Data mining in manufacturing: a review based on the kind of knowledge, Journal of Intelligent Manufacturing, vol.24, issue.3, pp.501-521, 2009.
DOI : 10.1007/s10845-008-0145-x

J. Pan and D. Tai, Implementing virtual metrology for in-line quality control in semiconductor manufacturing, International Journal of Systems Science, vol.19, issue.5, pp.461-470, 2009.
DOI : 10.1109/TSM.2007.907609

L. Huisman, Data Mining and Diagnosing IC Fails, 2005.

M. A. Karim, S. K. Halgamuge, A. J. Smith, and A. L. Hsu, Manufacturing Yield Improvement by Clustering, Proc. ICONIP, pp.526-534, 2006.
DOI : 10.1007/11893295_58

D. Braha and A. Shmilovici, Data mining for improving a cleaning process in the semiconductor industry, IEEE Transactions on Semiconductor Manufacturing, vol.15, issue.1, pp.91-101, 2002.
DOI : 10.1109/66.983448

D. Braha and A. Shmilovici, On the use of decision tree induction for discovery of interactions in a photolithographic process, IEEE Transactions on Semiconductor Manufacturing, vol.16, issue.4, pp.644-652, 2003.
DOI : 10.1109/TSM.2003.818959

D. Baek, I. Jeong, and C. H. Han, Application of Data Mining for Improving Yield in Wafer Fabrication System, Proc. ICCSA,v o l .4, pp.222-231, 2005.
DOI : 10.1007/11424925_25

D. Mackay-cambridge and U. K. , An Example Inference Task: Clustering, pp.284-292, 2003.

C. Chien, W. Wang, and J. Cheng, Data mining for yield enhancement in semiconductor manufacturing and an empirical study, Expert Systems with Applications, vol.33, issue.1, pp.192-198, 2007.
DOI : 10.1016/j.eswa.2006.04.014

L. Rokach and O. Maimon, Data Mining for Improving the Quality of Manufacturing: A Feature Set Decomposition Approach, Journal of Intelligent Manufacturing, vol.19, issue.7, pp.285-299, 2006.
DOI : 10.1007/s10845-005-0005-x

C. Huang and R. Chen, Application of new a priori algorithm MDNC to TFT-LCD array manufacturing yield improvement

W. Chen, S. Tseng, and C. Wang, A novel manufacturing defect detection method using association rule mining techniques, Expert Systems with Applications, vol.29, issue.4, pp.807-815, 2005.
DOI : 10.1016/j.eswa.2005.06.004

H. Sadoyan, A. Zakarian, and P. Mohanty, Data mining algorithm for manufacturing process control, The International Journal of Advanced Manufacturing Technology, vol.28, issue.3-4, pp.3-4, 2006.
DOI : 10.1007/s00170-004-2367-1

B. Ganter and R. Wille, Formal Concept Analysis: Mathematical Foundations, 1999.

S. Brin, R. Motwani, and C. Silverstein, Beyond market baskets: Generalizing association rules to correlations, Proc. SIGMOD Conf, pp.265-276, 1997.

M. Laporte, N. Novelli, R. Cicchetti, and L. Lakhal, Computing Full and Iceberg Datacubes Using Partitions, Proc. ISMIS, pp.244-254, 2002.
DOI : 10.1007/3-540-48050-1_28

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.468.7208

R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo, Fast discovery of association rules, Advances in Knowledge Discovery and Data Mining, pp.307-328, 1996.

X. Wu, C. Zhang, and S. Zhang, Efficient mining of both positive and negative association rules, ACM Transactions on Information Systems, vol.22, issue.3, pp.381-405, 2004.
DOI : 10.1145/1010614.1010616

G. Grahne, L. V. Lakshmanan, and X. Wang, Efficient mining of constrained correlated sets, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073), pp.512-521, 2000.
DOI : 10.1109/ICDE.2000.839450

M. Vel, Theory of Convex Structures, 1993.

H. Hirsh, Generalizing version spaces, Machine Learning, vol.2, issue.1, pp.5-46, 1994.
DOI : 10.1007/BF00993863

M. Spiegel and L. Stephens, Outline of Statistics, 1998.

D. Moore, Measures of lack of fit from tests of chi-squared type, Proc. EGC, pp.151-166, 1984.
DOI : 10.1016/0378-3758(84)90067-3

D. Laurent and N. Spyratos, Partition semantics for incomplete information in relational databases, Proc. SIGMOD Conf, pp.66-73, 1988.

H. Mannila and H. Toivonen, Levelwise search and borders of theories in knowledge discovery, Data Mining and Knowledge Discovery, vol.1, issue.3, pp.241-258, 1997.
DOI : 10.1023/A:1009796218281

F. Flouvat, F. D. Marchi, and J. Petit, A Thorough Experimental Study of Datasets for Frequent Itemsets, Fifth IEEE International Conference on Data Mining (ICDM'05), pp.162-169, 2005.
DOI : 10.1109/ICDM.2005.15

D. Pyle, Data Preparation for Data Mining, 1999.

O. Stepankova, P. Aubrecht, Z. Kouba, and P. Miksovsky, Preprocessing for data mining and decision support, " in Data Mining and Decision Support: Integration and Collaboration The Netherlands, pp.107-117, 2003.

H. Liu, F. Hussain, C. L. Tan, and M. Dash, Discretization: An enabling technique, Data Mining and Knowledge Discovery, vol.6, issue.4, pp.393-423, 2002.
DOI : 10.1023/A:1016304305535

G. Jenks, The data model concept in statistical mapping, International Yearbook of Cartography, pp.186-190, 1967.

W. Fisher, On Grouping for Maximum Homogeneity, Journal of the American Statistical Association, vol.40, issue.284, pp.789-798, 1958.
DOI : 10.2307/1907923