Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
The complexity of Boolean functions
The complexity of Boolean functions
Zero-suppressed BDDs for set manipulation in combinatorial problems
DAC '93 Proceedings of the 30th international Design Automation Conference
From rough set theory to evidence theory
Advances in the Dempster-Shafer theory of evidence
Binary decision diagrams and applications for VLSI CAD
Binary decision diagrams and applications for VLSI CAD
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Comparison of neofuzzy and rough neural networks
Information Sciences: an International Journal
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Extending naïve Bayes classifiers using long itemsets
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
International Journal of Human-Computer Studies - Special issue: 1969-1999, the 30th anniversary
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Small is beautiful: discovering the minimal set of unexpected patterns
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Rough set algorithms in classification problem
Rough set methods and applications
Mining frequent patterns with counting inference
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Making use of the most expressive jumping emerging patterns for classification
Knowledge and Information Systems
Incomplete Information: Structure, Inference, Complexity
Incomplete Information: Structure, Inference, Complexity
Rough Sets: Mathematical Foundations
Rough Sets: Mathematical Foundations
Rough set methods in feature selection and recognition
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
The Space of Jumping Emerging Patterns and Its Incremental Maintenance Algorithms
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Improving an Association Rule Based Classifier
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Dynamic Reducts as a Tool for Extracting Laws from Decisions Tables
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
An Incremental Learning Algorithm for Constructing Decision Rules
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Parallel Computation of Reducts
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Discretization Problem for Rough Sets Methods
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
RSES and RSESlib - A Collection of Tools for Rough Set Computations
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Exception Rule Mining with a Relative Interestingness Measure
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
An Efficient Single-Scan Algorithm for Mining Essential Jumping Emerging Patterns for Classification
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Approximate Reducts and Association Rules - Correspondence and Complexity Results
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Evaluation of an Algorithm for the Transversal Hypergraph Problem
WAE '99 Proceedings of the 3rd International Workshop on Algorithm Engineering
CAEP: Classification by Aggregating Emerging Patterns
DS '99 Proceedings of the Second International Conference on Discovery Science
Bounding Negative Information in Frequent Sets Algorithms
DS '01 Proceedings of the 4th International Conference on Discovery Science
Fast Algorithms for Mining Emerging Patterns
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Case studies: Public domain, multiple mining tasks systems: ROSETTA rough sets
Handbook of data mining and knowledge discovery
Fundamenta Informaticae
Data mining, rough sets and granular computing
Data mining, rough sets and granular computing
Mining Negative Association Rules
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
Mining Top.K Frequent Closed Patterns without Minimum Support
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Data mining based on rough sets
Data mining
Classification with Reject Option in Text Categorisation Systems
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
DeEPs: A New Instance-Based Lazy Discovery and Classification System
Machine Learning
Using emerging pattern based projected clustering and gene expression data for cancer detection
APBC '04 Proceedings of the second conference on Asia-Pacific bioinformatics - Volume 29
Incremental Maintenance on the Border of the Space of Emerging Patterns
Data Mining and Knowledge Discovery
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
Fundamenta Informaticae - Special issue on the 9th international conference on rough sets, fuzzy sets, data mining and granular computing (RSFDGrC 2003)
Essential classification rule sets
ACM Transactions on Database Systems (TODS)
Mining positive and negative association rules: an approach for confined rules
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
TFP: An Efficient Algorithm for Mining Top-K Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
Mining border descriptions of emerging patterns from dataset pairs
Knowledge and Information Systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
On the complexity of finding emerging patterns
Theoretical Computer Science - Pattern discovery in the post genome
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Fundamenta Informaticae - Contagious Creativity - In Honor of the 80th Birthday of Professor Solomon Marcus
Mining statistically important equivalence classes and delta-discriminative emerging patterns
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Application of elitist multi-objective genetic algorithm for classification rule generation
Applied Soft Computing
Jumping emerging patterns with negation in transaction databases - Classification and discovery
Information Sciences: an International Journal
An Approach to Unified Methodology of Combinational Switching Circuits
IEEE Transactions on Computers
Efficient Mining of Contrast Patterns and Their Applications to Classification
ICISIP '05 Proceedings of the 2005 3rd International Conference on Intelligent Sensing and Information Processing
An efficient ant colony optimization approach to attribute reduction in rough set theory
Pattern Recognition Letters
The Journal of Machine Learning Research
On the complexity of monotone dualization and generating minimal hypergraph transversals
Discrete Applied Mathematics
Probabilistic rough set approximations
International Journal of Approximate Reasoning
Fast Discovery of Minimal Sets of Attributes Functionally Determining a Decision Attribute
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Classification of Web Documents Using a Graph-Based Model and Structural Patterns
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Precision of Rough Set Clustering
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Efficient Discovery of Top-K Minimal Jumping Emerging Patterns
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
FUN: Fast Discovery of Minimal Sets of Attributes Functionally Determining a Decision Attribute
Transactions on Rough Sets IX
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
On combined classifiers, rule induction and rough sets
Transactions on rough sets VI
Efficient mining under rich constraints derived from various datasets
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Local projection in jumping emerging patterns discovery in transaction databases
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Adaptive classification with jumping emerging patterns
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Hierarchical clustering of non-euclidean relational data using indiscernibility-level
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Attribute set dependence in reduct computation
Transactions on computational science II
Condensed representation of EPs and patterns quantified by frequency-based measures
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Attribute set dependence in apriori-like reduct computation
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Local reducts and jumping emerging patterns in relational databases
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Finding minimal rough set reducts with particle swarm optimization
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Application of emerging patterns for multi-source bio-data classification and analysis
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Generating estimates of classification confidence for a case-based spam filter
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Association reducts: a framework for mining multi-attribute dependencies
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Exploiting maximal emerging patterns for classification
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Semantics of fuzzy sets in rough set theory
Transactions on Rough Sets II
Mining generalised emerging patterns
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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Contrast patterns are an essential element of classification methods based on data mining. Among many propositions, jumping emerging patterns (JEPs) have gained significant recognition due to their simplicity and strong discrimination capabilities. This thesis considers JEPs in terms of discovery and classification. The focus is put on their correspondence to the rough set theory. Transformations between transactional data and decision tables allow us to demonstrate relations of JEPs and global/local reducts. As a part of this discussion, we introduce the concept of a jumping emerging pattern with negation (JEPN). Our observations lead to two novel JEP mining methods based on local reducts: global condensation and local projection. Both attempt to decrease dimensionality of subproblems prior to reduct computation. We show that JEP mining can be reduced to the reduct set problem. The latter is addressed with a new approach, called RedApriori, that follows an Apriori candidate generation scheme and employs pruning based on the notion of attribute set dependence. In addition, we discuss different ways of storing pattern collections and propose a CC-Trie, a tree structure that ensures compactness of information and fast pattern lookups. A classic mining method for highly-supported JEPs employs a structure called a CP-Tree. We show how attribute set dependence can be employed in this approach to extend the pruning capabilities. Moreover, the problem of finding top-k most supported minimal JEPs is proposed. We discuss a solution that gradually raises minimal support while a CPTree is being mined. Small training sets are a challenge in classification. To improve accuracy, we propose AdaAccept, an adaptive classification meta-scheme that analyzes testing instances in turns. It employs an internal classifier with reject option that modifies itself only with accepted instances. Furthermore, we consider a concretization of this scheme in the field of emerging patterns, AdaptiveJEP-Classifier. Two adaptation methods, support adjustment and border recomputation, are put forward. The work has both theoretical and experimental character. The proposed methods and optimizations are evaluated and compared against solutions known in the literature.