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
Preference formulas in relational queries
ACM Transactions on Database Systems (TODS)
SaLSa: computing the skyline without scanning the whole sky
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Preference SQL: design, implementation, experiences
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A context-aware preference model for database querying in an ambient intelligent environment
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
Model-Driven Metadata for OLAP Cubes from the Conceptual Modelling of Data Warehouses
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
RoK: Roll-Up with the K-Means Clustering Method for Recommending OLAP Queries
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Preference-Based Recommendations for OLAP Analysis
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
A Conceptual Modeling Approach for OLAP Personalization
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
New Frontiers in business intelligence: distribution and personalization
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
A framework for OLAP content personalization
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems
Data & Knowledge Engineering
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Expressing preferences when querying databases is a natural way to avoid empty results and information flooding, and in general to rank results so that the user may first see the data that better match his tastes. In this paper we outline the main research issues to be faced in order to develop a system for handling user preferences on OLAP cubes.