Safety and translation of calculus queries with scalar functions
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A database perspective on knowledge discovery
Communications of the ACM
A framework for measuring changes in data characteristics
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data Mining: Introductory and Advanced Topics
Data Mining: Introductory and Advanced Topics
An Extension to SQL for Mining Association Rules
Data Mining and Knowledge Discovery
MSQL: A Query Language for Database Mining
Data Mining and Knowledge Discovery
The power of languages for the manipulation of complex values
The VLDB Journal — The International Journal on Very Large Data Bases
What Makes Patterns Interesting in Knowledge Discovery Systems
IEEE Transactions on Knowledge and Data Engineering
Domain-Independent Queries on Databases with External Functions
ICDT '95 Proceedings of the 5th International Conference on Database Theory
The 3W Model and Algebra for Unified Data Mining
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
A perspective on inductive databases
ACM SIGKDD Explorations Newsletter
Modeling and Language Support for the Management of Pattern-Bases
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
A unified and flexible framework for comparing simple and complex patterns
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
PSYCHO: a prototype system for pattern management
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Pattern-Miner: integrated management and mining over data mining models
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Monitoring Patterns through an Integrated Management and Mining Tool
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
The Panda framework for comparing patterns
Data & Knowledge Engineering
Data & Knowledge Engineering
AIKED'11 Proceedings of the 10th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
A relational view of pattern discovery
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
A unified framework for heterogeneous patterns
Information Systems
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Information overloading is today a serious concern that may hinder the potential of modern web-based information systems. A promising approach to deal with this problem is represented by knowledge extraction methods able to produce artifacts (also called patterns) that concisely represent data. Patterns are usually quite heterogeneous and voluminous. So far, little emphasis has been posed on developing an overall integrated environment for uniformly representing and querying different types of patterns. In this paper we consider the larger problem of modeling, storing, and querying patterns, in a database-like setting and use a Pattern-Base Management System (PBMS) for this purpose. Specifically, (a) we formally define the logical foundations for the global setting of pattern management through a model that covers data, patterns, and their intermediate mappings; (b) we present a formalism for pattern specification along with safety restrictions; and (c) we introduce predicates for comparing patterns and query operators.