TY - GEN
T1 - Processing of crisp and fuzzy measures in the fuzzy data warehouse for global natural resources
AU - Małysiak-Mrozek, Bozena
AU - Mrozek, Dariusz
AU - Kozielski, Stanisław
PY - 2010
Y1 - 2010
N2 - Fuzzy Data Warehouse (FDW) is a data repository, which contains fuzzy data and allows fuzzy processing of the data. Incorporation of fuzziness into data warehouse systems gives the opportunity to process data at higher level of abstraction and improves the analysis of imprecise data. It also gives the possibility to express business indicators in natural language using terms, like: high, low, about 10, almost all, etc., represented by appropriate membership functions. Fuzzy processing in data warehouses can affect many operations, like data selection, filtering, aggregation, and grouping. In the paper, we concentrate on various cases of data aggregation in our recently implemented fuzzy data warehouse storing consumption and requirement for global natural resources represented as crisp and fuzzy measures. We show several examples of data aggregation and filtering using the extended syntax of the SQL SELECT statement.
AB - Fuzzy Data Warehouse (FDW) is a data repository, which contains fuzzy data and allows fuzzy processing of the data. Incorporation of fuzziness into data warehouse systems gives the opportunity to process data at higher level of abstraction and improves the analysis of imprecise data. It also gives the possibility to express business indicators in natural language using terms, like: high, low, about 10, almost all, etc., represented by appropriate membership functions. Fuzzy processing in data warehouses can affect many operations, like data selection, filtering, aggregation, and grouping. In the paper, we concentrate on various cases of data aggregation in our recently implemented fuzzy data warehouse storing consumption and requirement for global natural resources represented as crisp and fuzzy measures. We show several examples of data aggregation and filtering using the extended syntax of the SQL SELECT statement.
KW - data aggregation
KW - decision support
KW - fuzzy data warehouse
KW - fuzzy sets
KW - membership function
KW - natural resources
KW - query language
UR - https://www.scopus.com/pages/publications/79551511206
U2 - 10.1007/978-3-642-13033-5_63
DO - 10.1007/978-3-642-13033-5_63
M3 - Conference contribution
AN - SCOPUS:79551511206
SN - 3642130321
SN - 9783642130328
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 616
EP - 625
BT - Trends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Proceedings
T2 - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010
Y2 - 1 June 2010 through 4 June 2010
ER -