A database perspective on knowledge discovery
Communications of the ACM
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
MSQL: A Query Language for Database Mining
Data Mining and Knowledge Discovery
Composition of Mining Contexts for Efficient Extraction of Association Rules
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Querying with Intrinsic Preferences
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Proceedings of the 17th International Conference on Data Engineering
The 3W Model and Algebra for Unified Data Mining
VLDB '00 Proceedings of the 26th 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
A New SQL-like Operator for Mining Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining N-most Interesting Itemsets
ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
Pattern Detection and Discovery
Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery
A Logical Database Mining Query Language
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Theoretical frameworks for data mining
ACM SIGKDD Explorations Newsletter
RankSQL: query algebra and optimization for relational top-k queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
ConQueSt: a Constraint-based Querying System for Exploratory Pattern Discovery
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Expressive power of an algebra for data mining
ACM Transactions on Database Systems (TODS)
Modeling and language support for the management of pattern-bases
Data & Knowledge Engineering
Constraint programming for itemset mining
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
An inductive database prototype based on virtual mining views
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Knowledge from Local Patterns with Global Constraints
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
IQL: a proposal for an inductive query language
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Towards a general framework for data mining
KDID'06 Proceedings of the 5th international conference on Knowledge discovery in inductive databases
Inductive database languages: requirements and examples
Knowledge and Information Systems
Towards an algebraic framework for querying inductive databases
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
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
A constraint language for declarative pattern discovery
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Cloud algebra for cloud database management system
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
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The elegant integration of pattern mining techniques into database remains an open issue. In particular, no language is able to manipulate data and patterns without introducing opaque operators or loop-like statement. In this paper, we cope with this problem using relational algebra to formulate pattern mining queries. We introduce several operators based on the notion of cover allowing to express a wide range of queries like the mining of frequent patterns. Beyond modeling aspects, we show how to reason on queries for characterizing and rewriting them for optimization purpose. Thus, we algebraically reformulate the principle of the levelwise algorithm.