Algorithms for clustering data
Algorithms for clustering data
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Knowledge Discovery in Databases
Knowledge Discovery in Databases
Efficient Mining of Association Rules in Distributed Databases
IEEE Transactions on Knowledge and Data Engineering
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Set-Oriented Mining for Association Rules in Relational Databases
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Multiple-Level Association Rules from Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Mining Generalized Association Rules
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Extracting optimal association rules over numeric attributes
ACM-SE 36 Proceedings of the 36th annual Southeast regional conference
Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Optimization of constrained frequent set queries with 2-variable constraints
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
RuleViz: a model for visualizing knowledge discovery process
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Multivariate discretization of continuous variables for set mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Transactions on Information Systems (TOIS)
Using quantitative information for efficient association rule generation
ACM SIGMOD Record
The segment support map: scalable mining of frequent itemsets
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Ordinal association rules for error identification in data sets
Proceedings of the tenth international conference on Information and knowledge management
Scalable frequent-pattern mining methods: an overview
Tutorial notes of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
An evolutionary algorithm to discover numeric association rules
Proceedings of the 2002 ACM symposium on Applied computing
Exploiting succinct constraints using FP-trees
ACM SIGKDD Explorations Newsletter
On the Complexity of Mining Quantitative Association Rules
Data Mining and Knowledge Discovery
Discovering calendar-based temporal association rules
Data & Knowledge Engineering - Special issue: Temporal representation and reasoning
Efficient Mining of Intertransaction Association Rules
IEEE Transactions on Knowledge and Data Engineering
Mining for Empty Rectangles in Large Data Sets
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Implication-Based Fuzzy Association Rules
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Fuzzy Functional Dependencies and Fuzzy Association Rules
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Construction of Adaptive Web-Applications from Reusable Components
EC-WEB '00 Proceedings of the First International Conference on Electronic Commerce and Web Technologies
Fuzzy Association Rules: Semantic Issues and Quality Measures
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Mining Association Rules in Preference-Ordered Data
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Mining Association Rules on Related Numeric Attributes
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Extending the Applicability of Association Rules
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
AViz: A Visualization System for Discovering Numeric Association Rules
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Neighborhood Dependencies for Prediction
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Discovering Numeric Association Rules via Evolutionary Algorithm
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
H-Rule Mining in Heterogeneous Databases
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
A template model for multidimensional inter-transactional association rules
The VLDB Journal — The International Journal on Very Large Data Bases
Mining for empty spaces in large data sets
Theoretical Computer Science - Database theory
An interactive visualization system for mining association rules
Data mining, rough sets and granular computing
A unifying semantic distance model for determining the similarity of attribute values
ACSC '03 Proceedings of the 26th Australasian computer science conference - Volume 16
Clustering intrusion detection alarms to support root cause analysis
ACM Transactions on Information and System Security (TISSEC)
Forecasting Association Rules Using Existing Data Sets
IEEE Transactions on Knowledge and Data Engineering
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A visualization model of interactive knowledge discovery systems and its implementations
Information Visualization
Efficient dynamic mining of constrained frequent sets
ACM Transactions on Database Systems (TODS)
ART: A Hybrid Classification Model
Machine Learning
A new histogram method for sparse attributes: the averaged rectangular attribute cardinality map
ISICT '03 Proceedings of the 1st international symposium on Information and communication technologies
Automatic Subspace Clustering of High Dimensional Data
Data Mining and Knowledge Discovery
Information Sciences—Informatics and Computer Science: An International Journal
SQUIRE: Sequential pattern mining with quantities
Journal of Systems and Software
Combined association rules for dealing with missing values
Journal of Information Science
Mining association rules from imprecise ordinal data
Fuzzy Sets and Systems
Mining pure linguistic associations from numerical data
International Journal of Approximate Reasoning
Fuzzy transform in the analysis of data
International Journal of Approximate Reasoning
First approach toward on-line evolution of association rules with learning classifier systems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
An information-theoretic approach to quantitative association rule mining
Knowledge and Information Systems
Mining fuzzy temporal patterns from process instances with weighted temporal graphs
International Journal of Data Analysis Techniques and Strategies
ACM SIGKDD Explorations Newsletter
MPSQAR: Mining Quantitative Association Rules Preserving Semantics
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Multi-objective genetic algorithms based automated clustering for fuzzy association rules mining
Journal of Intelligent Information Systems
Multi-level Frequent Pattern Mining
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
An algorithm to mine general association rules from tabular data
Information Sciences: an International Journal
QuantMiner: a genetic algorithm for mining quantitative association rules
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Genetic algorithm based framework for mining fuzzy association rules
Fuzzy Sets and Systems
Information Sciences: an International Journal
Mining multi-dimensional quantitative associations
INAP'01 Proceedings of the Applications of prolog 14th international conference on Web knowledge management and decision support
Association rule mining: models and algorithms
Association rule mining: models and algorithms
Speed up gradual rule mining from stream data! A B-Tree and OWA-based approach
Journal of Intelligent Information Systems
Mining fuzzy specific rare itemsets for education data
Knowledge-Based Systems
Finding association rules in semantic web data
Knowledge-Based Systems
A new clustering algorithm with the convergence proof
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Mining frequent patterns from univariate uncertain data
Data & Knowledge Engineering
Mining interesting XML-enabled association rules with templates
KDID'04 Proceedings of the Third international conference on Knowledge Discovery in Inductive Databases
Practical approximation of optimal multivariate discretization
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Quantitative and ordinal association rules mining (QAR mining)
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Effect of similar behaving attributes in mining of fuzzy association rules in the large databases
ICCSA'06 Proceedings of the 6th international conference on Computational Science and Its Applications - Volume Part I
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Mining quantitative association rules on overlapped intervals
ADMA'05 Proceedings of the First international conference on Advanced Data Mining and Applications
An extended two-phase architecture for mining time series data
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Querying multimedia presentations
Computer Communications
Detection of fuzzy association rules by fuzzy transforms
Advances in Fuzzy Systems - Special issue on Fuzzy Functions, Relations, and Fuzzy Transforms (2012)
Identifying stock similarity based on multi-event episodes
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
A clustering ensemble framework based on elite selection of weighted clusters
Advances in Data Analysis and Classification
Information Technology and Management
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We consider the problem of mining association rules over interval data (that is, ordered data for which the separation between data points has meaning). We show that the measures of what rules are most important (also called rule interest) that are used for mining nominal and ordinal data do not capture the semantics of interval data. In the presence of interval data, support and confidence are no longer intuitive measures of the interest of a rule. We propose a new definition of interest for association rules that takes into account the semantics of interval data. We developed an algorithm for mining association rules under the new definition and overview our experience using the algorithm on large real-life datasets.