Using Fuzzy Linguistic Representations to Provide Explanatory Semantics for Data Warehouses

Feng, Ling and Dillon, Tharam S. (2003) Using Fuzzy Linguistic Representations to Provide Explanatory Semantics for Data Warehouses. IEEE transactions on knowledge and data engineering, 15 (1). pp. 86-102. ISSN 10414347

Preview

PDF
1480Kb

Abstract:	A data warehouse integrates large amounts of extracted and summarized data from multiple sources for direct querying and analysis. While it provides decision makers with easy access to such historical and aggregate data, the real meaning of the data has been ignored. For example, "whether a total sales amount 1,000 items indicates a good or bad sales performance" is still unclear. From the decision makers' point of view, the semantics rather than raw numbers which convey the meaning of the data is very important. In this paper, we explore the use of fuzzy technology to provide this semantics for the summarizations and aggregates developed in data warehousing systems. A three layered data warehouse semantic model, consisting of quantitative (numerical) summarization, qualitative (categorical) summarization, and quantifier summarization, is proposed for capturing and explicating the semantics of warehoused data. Based on the model, several algebraic operators are defined. We also extend the SQL language to allow for flexible queries against such enhanced data warehouses.
Item Type:	Article
Copyright:	©2003 IEEE
Research Group:	Databases (DB)
Link to this item:	http://purl.utwente.nl/publications/46799
Official URL:	http://dx.doi.org/10.1109/TKDE.2003.1161584
Export this item as:	BibTeX EndNote HTML Citation Reference Manager

Show download statistics for this publication

Repository Staff Only: item control page

Metis ID: 216152