Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
The data warehouse toolkit: practical techniques for building dimensional data warehouses
The data warehouse toolkit: practical techniques for building dimensional data warehouses
starER: a conceptual model for data warehouse design
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Characterization of hierarchies and some operators in OLAP environment
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Database abstractions: aggregation and generalization
ACM Transactions on Database Systems (TODS)
Ontologies for conceptual modeling: their creation, use, and management
Data & Knowledge Engineering
Understanding semantic relationships
The VLDB Journal — The International Journal on Very Large Data Bases
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
A Logical Approach to Multidimensional Databases
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
WSD Algorithm Applied to a NLP System
NLDB '00 Proceedings of the 5th International Conference on Applications of Natural Language to Information Systems-Revised Papers
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
A Web Information Extraction System to DB Prototyping
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
What can Hierarchies do for Data Warehouses?
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Dimension Hierarchies Design from UML Generalizations and Aggregations
ER '01 Proceedings of the 20th International Conference on Conceptual Modeling: Conceptual Modeling
An Ontology-Based Framework for Generating and Improving Database Design
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
Maintaining Data Cubes under Dimension Updates
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Modelling strategic relationships for process reengineering
Modelling strategic relationships for process reengineering
AI Magazine
An analysis of additivity in OLAP systems
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
A UML profile for multidimensional modeling in data warehouses
Data & Knowledge Engineering - Special issue: ER 2003
A data warehouse engineering process
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
A taxonomy of inaccurate summaries and their management in OLAP systems
ER'05 Proceedings of the 24th international conference on Conceptual Modeling
Enriching data warehouse dimension hierarchies by using semantic relations
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
DC proposal: online analytical processing of statistical linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part II
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OLAP (On-Line Analytical Processing) operations, such as roll-up or drill-down, depend on data warehouse dimension hierarchies in order to aggregate information at different levels of detail and support the decision-making process required by final users. This is why it is crucial to capture adequate hierarchies in the requirement analysis stage. However, operational data could not be enough for supplying information to construct every level of these hierarchies. In this paper, we apply knowledge given by relationships among concepts from WordNet to overcome this problem. Therefore, richer dimension hierarchies will be specified in the data warehouse, and OLAP tools will be able to show proper information to improve decision-making process. Decision makers thus will be able to achieve their information needs for analysis. Finally, we will show the benefits of our approach by providing a case study in which a poor hierarchy is enriched with new levels of aggregation.