First-order preference theories and their applications
First-order preference theories and their applications
Preference structures and their numerical representations
Theoretical Computer Science
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A framework for expressing and combining preferences
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Can we push more constraints into frequent pattern mining?
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Preference queries in deductive databases
New Generation Computing
Querying with Intrinsic Preferences
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Mining Frequent Item Sets with Convertible Constraints
Proceedings of the 17th International Conference on Data Engineering
Proceedings of the 17th International Conference on Data Engineering
Functional Properties of Information Filtering
Proceedings of the 27th International Conference on Very Large Data Bases
An Analysis of Quantitative Measures Associated with Rules
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Preferences; Putting More Knowledge into Queries
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
WAR: Weighted Association Rules for Item Intensities
Knowledge and Information Systems
Preferential semantics for goals
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Reasoning with conditional ceteris paribus preference statements
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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The notion of preference naturally occurs in every context where one talks about human decisions or choice. Users, faced with a huge amount of data but often not equipped with a complete knowledge of the nature of the data, seek ways to obtain not necessarily all but the best or most preferred solutions. In this paper, we study preferences in the context of frequent pattern mining using the utility function approach. We also seek to provide a framework for investigating data mining problems involving preferences. We consider the problem of preference frequent pattern mining and N-best frequent pattern mining. We define preferences analytically, investigate their properties and classify them. We also provide some preference frequent pattern mining algorithms and show how they can be used for efficient N-best data mining.