Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
From contingency tables to various forms of knowledge in databases
Advances in knowledge discovery and data mining
Statistical methods for speech recognition
Statistical methods for speech recognition
Pruning and summarizing the discovered associations
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Principles of data mining
Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Bump hunting in high-dimensional data
Statistics and Computing
Pattern Discovery by Residual Analysis and Recursive Partitioning
IEEE Transactions on Knowledge and Data Engineering
Significance Tests for Patterns in Continuous Data
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
A Statistical Method for Finding Transcription Factor Binding Sites
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Interestingness of Discovered Association Rules in Terms of Neighborhood-Based Unexpectedness
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
Mining software repositories for comprehensible software fault prediction models
Journal of Systems and Software
Matching Partitions over Time to Reliably Capture Local Clusters in Noisy Domains
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Discovering Knowledge from Local Patterns with Global Constraints
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
Predicting going concern opinion with data mining
Decision Support Systems
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Agglomerating local patterns hierarchically with ALPHA
Proceedings of the 18th ACM conference on Information and knowledge management
Frequency-based views to pattern collections
Discrete Applied Mathematics - Special issue: Discrete mathematics & data mining II (DM & DM II)
Using interesting sequences to interactively build Hidden Markov Models
Data Mining and Knowledge Discovery
Guest Editorial: Global modeling using local patterns
Data Mining and Knowledge Discovery
Visualizing Situational Data: Applying Information Fusion for Detecting Social-Ecological Events
Social Science Computer Review
Krimp: mining itemsets that compress
Data Mining and Knowledge Discovery
A relational view of pattern discovery
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
Direct local pattern sampling by efficient two-step random procedures
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Pushing constraints to detect local patterns
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Pattern discovery tools for detecting cheating in student coursework
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Local pattern detection and clustering
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Features for learning local patterns in time-stamped data
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Knowledge-Based sampling for subgroup discovery
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Combining CSP and constraint-based mining for pattern discovery
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
Data mining in inductive databases
KDID'05 Proceedings of the 4th international conference on Knowledge Discovery in Inductive Databases
Performance of classification models from a user perspective
Decision Support Systems
Linear space direct pattern sampling using coupling from the past
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
20 years of pattern mining: a bibliometric survey
ACM SIGKDD Explorations Newsletter
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Data mining comprises two subdisciplines. One of these is based on statistical modelling, though the large data sets associated with data mining lead to new problems for traditional modelling methodology. The other, which we term pattern detection, is a new science. Pattern detection is concerned with defining and detecting local anomalies within large data sets, and tools and methods have been developed in parallel by several applications communities, typically with no awareness of developments elsewhere. Most of the work to date has focussed on the development of practical methodology, with little attention being paid to the development of an underlying theoretical base to parallel the theoretical base developed over the last century to underpin modelling approaches. We suggest that the time is now right for the development of a theoretical base, so that important common aspects of the work can be identified, so that key directions for future research can be characterised, and so that the various different application domains can benefit from the work in other areas. We attempt describe a unified approach to the subject, and also attempt to provide theoretical base on which future developments can stand.