Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 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
Query driven knowledge discovery in multidimensional data
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
A survey of logical models for OLAP databases
ACM SIGMOD Record
Use and reuse of association rules in an OLAP environment
Proceedings of the 2000 information resources management association international conference on Challenges of information technology management in the 21st century
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Modeling Multidimensional Databases
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Generating Fuzzy Summaries from Fuzzy Multidimensional Databases
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Mining Fuzzy Quantitative Association Rules
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Data mining in soft computing framework: a survey
IEEE Transactions on Neural Networks
Data mining by attribute generalization with fuzzy hierarchies in fuzzy databases
Fuzzy Sets and Systems
Fuzzy methods in machine learning and data mining: Status and prospects
Fuzzy Sets and Systems
Fuzzy sets in machine learning and data mining
Applied Soft Computing
Expert Systems with Applications: An International Journal
Fuzzy machine learning and data mininga
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
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Intelligent data analysis faces the problem of the huge amounts of data. More and more, database management systems are required to deal with this large repositories. In this framework, multidimensional databases are particularly adapted. They have emerged to support the OLAP framework. OLAP, standing for On Line Analytical Processing, is devoted to the fast analysis of multidimensional data. This model has been recently extended to the treatment of imperfect data and flexible queries. In this paper, we propose a new architecture based on fuzzy multidimensional databases to generate fuzzy summaries. This approach offers two main advantages. First, it provides a scalable framework due to the use of a database management system. Second, the introduction of fuzziness provides a theoretical framework to handle data from the real world and flexible queries. The chosen data mining tool is the generation of linguistic summaries. This kind of rules is a more understandable knowledge for the user than classical association rules. A user-friendly system is provided. This approach is compared to existing frameworks devoted to data analysis with association rules or fuzzy summaries. We insist on the fact that this model generalizes the classical one. It provides a framework to handle all classical crisp cases, since fuzzy set theory provides means to handle imperfect and classical data. Thus this method may be applied on classical data to generate fuzzy summaries.