An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Principles of distributed database systems (2nd ed.)
Principles of distributed database systems (2nd ed.)
A framework for expressing and combining preferences
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Advanced visualization for OLAP
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
Preference formulas in relational queries
ACM Transactions on Database Systems (TODS)
Personalization of Queries in Database Systems
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Index Selection for Databases: A Hardness Study and a Principled Heuristic Solution
IEEE Transactions on Knowledge and Data Engineering
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
An evolutionary approach to schema partitioning selection in a data warehouse
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
A user-driven data warehouse evolution approach for concurrent personalized analysis needs
Integrated Computer-Aided Engineering
A framework for recommending OLAP queries
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
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
Recommending Multidimensional Queries
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Preference-Based Recommendations for OLAP Analysis
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Query recommendations for OLAP discovery driven analysis
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
A Conceptual Modeling Approach for OLAP Personalization
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
Pixelizing data cubes: a block-based approach
VIEW'06 Proceedings of the 1st first visual information expert conference on Pixelization paradigm
A framework for OLAP content personalization
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Mining preferences from OLAP query logs for proactive personalization
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Semantics and usage statistics for multi-dimensional query expansion
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Performing groupization in data warehouses: which discriminating criterion to select?
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Multi-dimensional navigation modeling using BI analysis graphs
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
Efficiently compressing OLAP data cubes via R-tree based recursive partitions
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
Query Recommendations for OLAP Discovery-Driven Analysis
International Journal of Data Warehousing and Mining
| Hi-index | 0.00 |
OLAP users heavily rely on visualization of query answers for their interactive analysis of massive amounts of data. Very often, these answers cannot be visualized entirely and the user has to navigate through them to find relevant facts.In this paper, we propose a framework for personalizing OLAP queries. In this framework, the user is asked to give his (her) preferences and a visualization constraint, that can be for instance the limitations imposed by the device used to display the answer to a query. Given this, for each query, our method computes the part of the answer that respects both the user preferences and the visualization constraint. In addition, a personalized structure for the visualization is proposed.