Utilisation de la connaissance du domaine pour la découverte de g` enes co-régulés Mining association rules between sets of items in large databases, 158Chapitre 12 Buneman, P. et Jajodia, S., ´ editeurs : SIGMOD Conference, pp.207-216, 1993. ,
Fast discovery of association rules, Advances in Knowledge Discovery and Data Mining, pp.307-328, 1996. ,
Fast algorithms for mining association rules in large databases, pp.487-499, 1994. ,
Mining sequential patterns, Proceedings of the Eleventh International Conference on Data Engineering, pp.3-14, 1995. ,
DOI : 10.1109/ICDE.1995.380415
Self-renewal and solid tumor stem cells, Oncogene, vol.23, pp.7274-7282, 2004. ,
DOI : 10.1038/sj.onc.1207947
Constraint Relaxations for Discovering Unknown Sequential Patterns, Proceedings of the Third International Workshop on Knowledge Discovery inInductive Databases, pp.11-32, 2004. ,
DOI : 10.1007/978-3-540-31841-5_2
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.108.4446
Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets, Computational Logic, volume 1861 de Lecture Notes in Computer Science, pp.972-986, 2000. ,
DOI : 10.1007/3-540-44957-4_65
URL : https://hal.archives-ouvertes.fr/hal-00467751
Efficiently mining long patterns from databases, Proceedings ACM SIGMOD International Conference on Management of Data, pp.85-93, 1998. ,
DOI : 10.1145/276304.276313
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.107.1120
The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery, Proc. of the Workshop on Inductive Databases and Constraint Based Mining (IDW'05), 2005. ,
DOI : 10.1007/11615576_1
Strong association rule mining for large gene expression data analysis : A case study on human sage data, Genome Biology, vol.3, issue.12, p.16, 2002. ,
URL : https://hal.archives-ouvertes.fr/hal-00194295
Bottom-up computation of sparse and iceberg cubes Lattices theory Interestingness is not a dichotomy : Introducing softness in constrained pattern mining Pushing constraints to detect local patterns editeurs : Local Pattern Detection, SIGMOD Conference, pp.359-370, 1967. ,
Anticipated data reduction in constrained pattern mining, Lavrac PKDD, volume 2838 de Lecture Notes in Computer Science, pp.59-70 ,
FP-bonsai : The art of growing and pruning small FP-trees Advances in Knowledge Discovery and Data Mining, 8th Pacific-Asia Conference, Proceedings, volume 3056 de Lecture Notes in Computer Science, pp.155-160, 2004. ,
On closed constrained frequent pattern mining Pushing tougher constraints in frequent pattern mining Comparison of medulloblastoma and normal neural transcriptomes identifies a restricted set of activated genes, Proceedings of the 4th IEEE International Conference on Data Mining editeurs : Advances in Knowledge Discovery and Data Mining, 9th Pacific-Asia Conference, PAKDD 2005 Proceedings, volume 3518 de Lecture Notes in Computer Science, pp.1-4, 2003. ,
Induction of Association Rules: Apriori Implementation, 15th Conference on Computational Statistics, pp.395-400, 2002. ,
DOI : 10.1007/978-3-642-57489-4_59
Frequent Closures as a Concise Representation for Binary Data Mining, Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp.62-73, 2000. ,
DOI : 10.1007/3-540-45571-X_9
Approximation of frequency queris by means of free-sets Principles of Data Mining and Knowledge Discovery Using constraint for itemset mining : Should we prune or not, 4th European Conference Proceedings, volume 1910 de Lecture Notes in Computer Science, pp.75-85, 2000. ,
Mining free itemsets under constraints, Proceedings 2001 International Database Engineering and Applications Symposium, pp.322-329, 2001. ,
DOI : 10.1109/IDEAS.2001.938100
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.664
The process of knowledge discovery in databases, Advances in Knowledge Discovery and Data Mining, pp.37-57, 1996. ,
Using association rules for product assortment decisions, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '99, pp.254-260, 1999. ,
DOI : 10.1145/312129.312241
DualMiner, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, 2002. ,
DOI : 10.1145/775047.775054
MAFIA: a maximal frequent itemset algorithm for transactional databases, Proceedings 17th International Conference on Data Engineering, pp.443-452, 2001. ,
DOI : 10.1109/ICDE.2001.914857
Mining all non-derivable frequent itemsets, proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD'02), pp.74-85, 2002. ,
Minimal k-free representations of frequent sets, proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'03), pp.71-82, 2003. ,
A Survey on Condensed Representations for Frequent Sets, Lecture Notes in Computer Science, vol.3848, pp.64-80, 2004. ,
DOI : 10.1007/11615576_4
Towards a formal framework for mining general patterns from ordered data, MRDM 2003 2nd Workshop on Multi-Relational Data Mining Preliminary schedule, 2003. ,
Mining closed and maximal frequent subtrees from databases of labeled rooted trees, IEEE Trans. Knowl. Data Eng, vol.17, issue.2, pp.190-202, 2005. ,
Rule induction with CN2: Some recent improvements, Proc. Fifth European Working Session on Learning, pp.151-163, 1991. ,
DOI : 10.1007/BFb0017011
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.24.1700
A relational model of data for large shared data banks, Communications of the ACM, vol.13, issue.6, pp.377-387, 1970. ,
DOI : 10.1145/362384.362685
Mining the top-k frequent itemset with minimum length m, 2001. ,
Monotone constraints in frequent tree mining, editeurs : the 14 th Annual Machine Learning Conference of Belgium and the Netherlands, pp.13-20, 2005. ,
Frequent pattern discovery in first-order logic Human primitive neuroectodermal tumour cells behave as multipotent neural precursors in response to FGF2, Thèse de doctorat, pp.1663-1672, 1998. ,
UCI repository of machine learning databases, 1998. ,
Efficient mining of emerging patterns : discovering trends and differences, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining (KDD'99), pp.43-52, 1999. ,
CAEP: Classification by Aggregating Emerging Patterns, 1721 de Lecture Notes in Computer Science, pp.30-42, 1999. ,
DOI : 10.1007/3-540-46846-3_4
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.134.2653
ECCLAT : a New Approach of Clusters Discovery in Categorical Data Emerging overlapping clusters for characterizing the stage of fibrosis, the 22nd Int. Conf. on Knowledge Based Systems and Applied Artificial Intelligence (ES'02) proceedings of the workshop Discovery Challenge, PKDD'05, pp.177-190, 2002. ,
Finding all frequent patterns starting from the closure, editeurs : Advanced Data Mining and Applications, First International Conference Proceedings, volume 3584 de Lecture Notes in Computer Science, pp.67-74, 2005. ,
Bifold constraintbased mining by simultaneous monotone and anti-monotone checking, Proceedings of the 5th IEEE International Conference on Data Mining, pp.27-30, 2005. ,
DOI : 10.1109/icdm.2005.35
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.3276
Knowledge discovery and data mining : Towards a unifying framework, KDD, pp.82-88, 1996. ,
Version spaces in constraint-based data mining ABS : Adaptive borders search of frequent itemsets, de CEUR Workshop Proceedings. CEUR-WS.org, 2003. ,
Mining n-most interesting itemsets Two basic algorithms in concept analysis, editeurs : ISMIS, volume 1932 de Lecture Notes in Computer Science Preprint 831, pp.59-67, 1984. ,
SPIRIT : Sequential pattern mining with regular expression constraints, The VLDB Journal, pp.223-234, 1999. ,
DOI : 10.1109/tkde.2002.1000341
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.136.7052
Guest editorial to the special issue on data stream processing, VLDB J, vol.13, issue.4, p.317, 2004. ,
Condensed Representations for Sets of Mining Queries, proceedings of KDID'02, 2002. ,
DOI : 10.1016/S0306-4379(99)00003-4
Clustering Transactional Data, editeurs : PKDD, volume 2431 de Lecture Notes in Computer Science, pp.175-187, 2002. ,
DOI : 10.1007/3-540-45681-3_15
URL : http://puma.isti.cnr.it/rmydownload.php?filename=cnr.isti/cnr.cnuce/2001-B4-003/2001-B4-003.pdf
Survey on frequent pattern mining, 2003. ,
GenMax: An Efficient Algorithm for Mining Maximal Frequent Itemsets, Data Mining and Knowledge Discovery, vol.129, issue.2, pp.223-242, 2005. ,
DOI : 10.1007/s10618-005-0002-x
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
Data cube: a relational aggregation operator generalizing GROUP-BY, CROSS-TAB, and SUB-TOTALS, Proceedings of the Twelfth International Conference on Data Engineering, pp.152-159, 1996. ,
DOI : 10.1109/ICDE.1996.492099
Data cube: a relational aggregation operator generalizing GROUP-BY, CROSS-TAB, and SUB-TOTALS, Proceedings of the Twelfth International Conference on Data Engineering, pp.29-53, 1997. ,
DOI : 10.1109/ICDE.1996.492099
URL : http://arxiv.org/abs/cs/0701155
Data mining, hypergraph transversals, and machine learning, PODS, pp.209-216, 1997. ,
DOI : 10.1145/263661.263684
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.46.1843
Prince: An Algorithm for Generating Rule Bases Without Closure Computations, editeurs : DaWaK, volume 3589 de Lecture Notes in Computer Science, pp.346-355, 2005. ,
DOI : 10.1007/11546849_34
URL : https://hal.archives-ouvertes.fr/hal-00397430
Clustering based on association rule hypergraphs, proceedings of the workshop on Research Issues on Data Mining And Knowledge Discovery, 1997. ,
Efficient computation of iceberg cubes with complex measures, ACM SIGMOD International Conf. on Management of Data, 2001. ,
Mining frequent patterns without candidate generation, editeurs : SIGMOD Conference, pp.1-12, 2000. ,
DOI : 10.1145/342009.335372
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.35.2678
Mining top-k frequent closed patterns without minimum support, ICDM, pp.211-218, 2002. ,
Mining association rules : Deriving a superior algorithm by analyzing today's approaches Principles of Data Mining and Knowledge Bibliographie Discovery, 4th European Conference Proceedings, volume 1910 de Lecture Notes in Computer Science, pp.159-168, 2000. ,
TF2P-growth : Frequent itemset mining algorithm without any thresholds, Proc. of Workshop on Alternative Techniques for Data Mining and Knowledge Discovery, 2004. ,
Optimizing hypergraph transversal computation with an anti-monotone constraint, Proceedings of the 2007 ACM symposium on Applied computing , SAC '07, 2007. ,
DOI : 10.1145/1244002.1244104
A database perspective on knowledge discovery, Communication of the ACM, pp.58-64, 1996. ,
DOI : 10.1145/240455.240472
Optimisation dereqù etes inductives : applicationàapplication`applicationà l'extraction sous contraintes de r` egles d'association, Thèse de doctorat, 2002. ,
Database transposition for constrained closed pattern mining, proceedings of Third International Workshop on Knowledge Discovery in Inductive Databases (KDID) co-located with ECML/PKDD, 2004. ,
Identitag, a relational database for sage tag identification and interspecies comparison of sage libraries, BMC Bioinformatics, vol.5, issue.1, p.143, 2004. ,
DOI : 10.1186/1471-2105-5-143
URL : https://hal.archives-ouvertes.fr/hal-00193784
How to quickly find a witness, Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, pp.272-283, 2003. ,
Mining Plausible Patterns from Genomic Data, 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06), pp.90-101, 2006. ,
DOI : 10.1109/CBMS.2006.116
URL : https://hal.archives-ouvertes.fr/hal-00324807
Molecular feature mining in HIV data, Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '01, pp.136-143, 2001. ,
DOI : 10.1145/502512.502533
Frequent subgraph discovery, Proceedings 2001 IEEE International Conference on Data Mining, pp.313-320, 2001. ,
DOI : 10.1109/ICDM.2001.989534
Efficient dynamic mining of constrained frequent sets, ACM Transactions on Database Systems, vol.28, issue.4, pp.337-389, 2003. ,
DOI : 10.1145/958942.958944
An algebra for inductive query evaluation, Third IEEE International Conference on Data Mining, pp.147-154, 2003. ,
DOI : 10.1109/ICDM.2003.1250914
An efficient algorithm for mining string databases under constraints, Knowledge Discovery in Inductive Databases, Proceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases de Lecture Notes in Computer Science, pp.108-129, 2004. ,
Exploiting succinct constraints using FP-trees, ACM SIGKDD Explorations Newsletter, vol.4, issue.1, pp.40-49, 2002. ,
DOI : 10.1145/568574.568581
CMAR : Accurate and efficient classification based on multiple class-association rules, Proceedings of the 2001 IEEE International Conference on Data Mining, 2001. ,
In vivo transcriptional profile analysis reveals RNA splicing and chromatin remodeling as prominent processes for adult neurogenesis, Molecular and Cellular Neuroscience, vol.31, issue.1, pp.131-148, 2006. ,
DOI : 10.1016/j.mcn.2005.10.005
Integrating classification and association rule mining, KDD, pp.80-86, 1998. ,
Improving an Association Rule Based Classifier, 4th European Conference Proceedings, volume 1910 de Lecture Notes in Computer Science, pp.504-509, 2000. ,
DOI : 10.1007/3-540-45372-5_58
Sam68, the KH domaincontaining superSTAR, Biochim Biophys Acta, vol.1653, pp.73-86, 2003. ,
Inductive databases and condensed representations for data mining, International Logic Programming Symposium, pp.21-30, 1997. ,
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
Discovering frequent episodes in sequences, KDD, pp.210-215, 1995. ,
GOToolbox : functional investigation of gene datasets based on gene ontology, Genome Biology, vol.5, issue.12, p.101, 2004. ,
DOI : 10.1186/gb-2004-5-12-r101
A new SQL-like operator for mining association rules, pp.122-133, 1996. ,
Separating structure from interestingness Advances in Knowledge Discovery and Data Mining, 8th Pacific-Asia Conference, Proceedings, volume 3056 de Lecture Notes in Computer Science, pp.476-485, 2004. ,
Generalization as search, Artificial Intelligence, vol.18, issue.2, pp.203-226, 1982. ,
DOI : 10.1016/0004-3702(82)90040-6
Local Pattern Detection, International Seminar, de Lecture Notes in Computer Science, 2004. ,
Traversing itemset lattice with statistical metric pruning, PODS, pp.226-236, 2000. ,
Exploratory mining and pruning optimizations of constrained association rules, Proceedings ACM SIGMOD International Conference on Management of Data, pp.13-24, 1998. ,
Application of matrix clustering to web log analysis and access prediction, proceedings of the WebKDD workshop (WebKDD'01) co-located with the 7th ACM SIGKDD International Conference on Knowledge Discovery in Databases (KDD'01), 2001. ,
Discovering Frequent Closed Itemsets for Association Rules, Lecture Notes in Computer Science, 1999. ,
DOI : 10.1007/3-540-49257-7_25
URL : https://hal.archives-ouvertes.fr/hal-00467747
Can we push more constraints into frequent pattern mining ?, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, pp.350-354, 2000. ,
Constrained frequent pattern mining, ACM SIGKDD Explorations Newsletter, vol.4, issue.1, pp.31-39, 2002. ,
DOI : 10.1145/568574.568580
Mining frequent item sets with convertible constraints, ICDE, pp.433-442, 2001. ,
Pushing Convertible Constraints in Frequent Itemset Mining, Data Mining and Knowledge Discovery, vol.8, issue.3, pp.227-252, 2004. ,
DOI : 10.1023/B:DAMI.0000023674.74932.4c
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.205.3940
CLOSET : An efficient algorithm for mining frequent closed itemsets, In ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, pp.21-30, 2000. ,
Prefixspan : Mining sequential patterns by prefix-projected growth, ICDE, pp.215-224, 2001. ,
Mining sequential patterns with constraints in large databases, Proceedings of the eleventh international conference on Information and knowledge management , CIKM '02, pp.18-25, 2002. ,
DOI : 10.1145/584792.584799
From Local Pattern Mining to Relevant Bi-cluster Characterization, de Lecture Notes in Computer Science, pp.293-304, 2005. ,
DOI : 10.1007/11552253_27
Discovery in multi-attribute data with user-defined constraints, ACM SIGKDD Explorations Newsletter, vol.4, issue.1, pp.56-64, 2002. ,
DOI : 10.1145/568574.568583
Discovery, analysis and presentation of strong rules, Knowledge Discovery in Databases, pp.229-248, 1991. ,
Induction of decision trees, Machine Learning, vol.1, issue.1, pp.81-106, 1986. ,
DOI : 10.1007/BF00116251
The levelwise version space algorithm and its application to molecular fragment finding Attribute similarity and event sequence similarity in data mining, Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp.853-862, 1998. ,
Term-weighting approaches in automatic text retrieval, Information Processing & Management, vol.24, issue.5, pp.513-523, 1988. ,
DOI : 10.1016/0306-4573(88)90021-0
Generation of rules with certainty and confidence factors from incomplete and incoherent learning bases, Proc. of the European Knowledge Acquisition Workshop (EKAW'88), pp.28-29, 1988. ,
/NonO - multi-functional nuclear proteins, FEBS Letters, vol.12, issue.2, pp.109-114, 2002. ,
DOI : 10.1016/S0014-5793(02)03447-6
Item Sets That Compress, SIAM conference on data mining, 2006. ,
DOI : 10.1137/1.9781611972764.35
Rule induction using information theory, editeurs : Knowledge Discovery in Databases, pp.159-176, 1991. ,
An efficient framework for mining flexible constraints Advances in Knowledge Discovery and Data Mining, 9th Pacific-Asia Conference, PAKDD, Proceedings, volume 3518 de Lecture Notes in Computer Science, pp.661-671, 2005. ,
Exploiting Virtual Patterns for Automatically Pruning the Search Space, Knowledge Discovery in Inductive Databases, 4th International Workshop, KDID 2005 de Lecture Notes in Computer Science, pp.202-221, 2005. ,
DOI : 10.1007/3-540-49257-7_25
URL : https://hal.archives-ouvertes.fr/hal-00324841
Optimizing constraintbased mining by automatically relaxing constraints, Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), pp.777-780, 2005. ,
URL : https://hal.archives-ouvertes.fr/hal-00324838
Condensed Representation of Emerging Patterns, 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp.127-132, 2004. ,
DOI : 10.1007/978-3-540-24775-3_16
URL : https://hal.archives-ouvertes.fr/hal-00324836
Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures, Knowledge Discovery in Inductive Databases, Proceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases de Lecture Notes in Computer Science, pp.173-190, 2004. ,
DOI : 10.1007/978-3-540-31841-5_10
URL : https://hal.archives-ouvertes.fr/hal-00324835
Représentation condensée de motifsémergentsmotifsémergents, Revue des Nouvelles Technologies de l'Information, pp.265-276, 2004. ,
Using emerging patterns from clusters to characterize social subgroups of patients affected by atherosclerosis, proceedings of the workshop Discovery Challenge, ECML-PKDD'04, 2004. ,
URL : https://hal.archives-ouvertes.fr/hal-00324839
CHARM : an efficient algorithm for closed association rule mining, 1999. ,
Parallel and distributed association mining: a survey, IEEE Concurrency, vol.7, issue.4, pp.14-25, 1999. ,
DOI : 10.1109/4434.806975
Scalable algorithms for association mining, IEEE Transactions on Knowledge and Data Engineering, vol.12, issue.3, pp.372-390, 2000. ,
DOI : 10.1109/69.846291
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.28.656
Efficiently mining frequent trees in a forest, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, pp.71-80, 2002. ,
DOI : 10.1145/775047.775058
XRules, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.316-325, 2003. ,
DOI : 10.1145/956750.956787
Towards generic pattern mining ´ editeurs : Formal Concept Analysis, Third International Conference Proceedings, volume 3403 de Lecture Notes in Computer Science, pp.1-20, 2005. ,
DOI : 10.1007/978-3-540-32262-7_1
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.6205
Molecular insights into mental retardation : multiple functions for the fragile X mental retardation protein ?, Curr Issues Mol Biol, vol.6, pp.73-88, 2004. ,
Relational subgroup discovery for gene expression data mining, EMBEC : 3rd IFMBE European Medical & Biological Engineering Conf, 2005. ,
Information-Based Classification by Aggregating Emerging Patterns, editeurs : Intelligent Data Engineering and Automated Learning -IDEAL 2000, Data Mining, Financial Engineering, and Intelligent Agents, Second International Conference, 2000. ,
DOI : 10.1007/3-540-44491-2_8