Lossless reduction of datacubes using partitions

International Journal of Data Warehousing and Mining

Volumn 5, Issue 1, 2009, Pages 18-35

  Casali, Alain ^a   Nedjar, Sébastien ^a   Cicchetti, Rosine ^a   Lakhal, Lotfi ^a   Novelli, Noël ^a  

^a AIX MARSEILLE UNIVERSITY   (France)

Author keywords

Concept lattices; Datacubes; Olap; Partitions

Indexed keywords

DATA WAREHOUSES; DIGITAL STORAGE; PARTITIONS (BUILDING);

AGGREGATED DATUM; ANALYTICAL EVALUATION; CONCEPT LATTICES; CONCISE REPRESENTATIONS; DATACUBES; OLAP; RECENT RESEARCHES; REDUCTION METHOD;

GEOMETRY;

EID: 69249248901     PISSN: 15483924     EISSN: 15483932     Source Type: Journal    
DOI: 10.4018/jdwm.2009010102     Document Type: Article

References (41)

1. Bayardo, R., Goethals, B., & Zaki, M. J. (2003). Workshop on Frequent Itemset Mining Implementations. Bayardo, Roberto; Goethals, Bart; Zaki, Mohammed J.
2. Beyer, K. S., & Ramakrishnan, R. (1999). Bottom- Up Computation of Sparse and Iceberg CUBEs. Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data (SIGMOD'99), (pp. 359-370). Dallas, USA.
3. Casali, A., Cicchetti, R., & Lakhal, L. (2003a). Cube Lattices: A Framework for Multidimensional Data Mining. Proceedings of the Third SIAM International Conference on Data Mining (SDM'03). San Francisco, USA.
4. Casali, A., Cicchetti, R., & Lakhal, L. (2003b). Extracting semantics from data cubes using cube transversals and closures. Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'03), (pp. 69-78). Washington, USA.
5. Casali, A., Cicchetti, R., Lakhal, L., & Novelli, N. (2006). Lossless reduction of datacubes. Proceedings of the 17th international conference on database and expert systems applications (DEXA'06), (pp. 409-419). Kraków, Poland.
6. Casali, A., Nedjar, S., Cicchetti, R., & Lakhal, L. (2007). Convex cube: Towards a unified structure for multidimensional databases. Proceedings of the 18th international conference on database and expert systems applications (DEXA'07), (pp. 572-581). Regensburg, Germany.
7. Chaudhuri, S., & Dayal, U. (1997). An Overview of Data Warehousing and OLAP Technology. Sigmod record, 26 (1), 65-74. (Pubitemid 127458202)
8. Ganter, B., & Wille, R. (1999). Formal Concept Analysis: Mathematical Foundations. Springer.
9. Gilbert, A., Kotidis, Y., Muthukrishnan, S., & Strauss, M. (2001). Surfing Wavelets on Streams: One-Pass Summaries for Approximate Queries. Proceedings of 27th International Conference on Very Large Data Bases (VLDB'01), (pp. 79-88). Roma, Italy.
10. Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., et al. (1997). Data Cube: A Relational Aggregation Operator Generalizing Group-by, Cross-Tab, and Sub Totals. Data Mining and Knowledge Discovery, 1 (1), 29-53. (Pubitemid 127721235)
11. Gupta, H., & Mumick, I. (2005). Selection of Views to Materialize in a Data Warehouse. IEEE Transactions on Knowledge and Data Engineering (TKDE), 17 (1), 24-43.
12. Han, J., & Kamber, M. (2000). Data Mining: Concepts and Techniques. Morgan Kaufmann.
13. Han, J., Pei, J., Dong, G., & Wang, K. (2001). Efficient Computation of Iceberg Cubes with Complex Measures. Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data (SIGMOD'01), (pp. 441-448). Santa Barbara, USA.
14. Harinarayan, V., Rajaraman, A., & Ullman, J. (1996). Implementing data cubes efficiently. Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data (SIGMOD'96), (pp. 205-216). Montreal, Canada.
15. Hurtado, C. A., & Mendelzon, A. O. (2002). OLAP dimension constraints. Proceedings of the Twentyfirst ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS'02), (pp. 169-179). Madison, USA.
16. Kotidis, Y., & Roussopoulos, N. (1998). An alternative storage organization for rOLAP aggregate views based on cubetrees. Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data (SIGMOD'98), (pp. 249-258).Seattle, USA.
17. Kotidis, Y., & Roussopoulos, N. (1999). DynaMat: A Dynamic View Management System for Data Warehouses. Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data (SIGMOD'99), (pp. 371-382). Philadelphia, USA.
18. Kudryavcev, Y. (2006). Efficient algorithms for mOLAP data storage and query processing. In Spring colloquium for young researchers in databases and information systems, syrcodis.
19. Lakshmanan, L., Pei, J., & Han, J. (2002). Quotient cube: How to summarize the semantics of a data cube. Proceedings of 28th International Conference onVery Large Data Bases (VLDB'02), (pp. 778-789). Hong Kong, China.
20. Lakshmanan, L., Pei, J., & Zhao, Y. (2003). QC-Trees: An Efficient Summary Structure for Semantic OLAP. Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data (SIGMOD'03), (pp. 64-75). San Diego, USA.
21. Laurent, D., & Spyratos, N. (1988). Partition semantics for incomplete information in relational databases. Proceedings of the 1988 ACM SIGMOD International Conference on Management of Data (SIGMOD'88), (pp. 66-73). Chicago, USA.
22. Li, S.-E., & Wang, S. (2005). Semi-closed cube: An effective approach to trading off data cube size and query response time. Journal of Computer Science and Technology, 20 (3), 367-372.
23. Lopes, S., Petit, J. M., & Lakhal, L. (2002). Functionaland Approximate Dependency Mining: Databases and FCA points of View. Journal of Experimental and Theoretical Artificial Intelligence (JETAI), 14 (2-3), 93-114.
24. Mannila, H., & Toivonen, H. (1996). Multiple Uses of Frequent Sets and Condensed Representations: Extended Abstract. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD'96), (pp. 189-194). Portland, USA.
25. Mitchell, T. M. (1996). Machine learning. MacGraw- Hill Series in Computer Science.
26. Morfonios, K., & Ioannidis, Y. E. (2006). Cure for cubes: Cubing using a rOLAP engine. Proceedings of the 32nd International Conference on Very Large Data Bases, (pp. 379-390). Seoul, Korea.
27. Nedjar, S., Casali, A., Cicchetti, R., & Lakhal, L. (2007). Emerging cubes for trends analysis in OLAP databases. Data Warehousing and Knowledge Discovery, 9th International Conference (DaWaK'07), (pp. 135-144). Regensburg, Germany.
28. Pasquier, N., Bastide, Y., Taouil, R., & Lakhal, L. (1999). Discovering Frequent Closed Itemsets for Association Rules. Proceedings of the 7th International Conference on Database Theory (ICDT '99), (pp. 398-416). Jerusalem, Israel.
29. Pedersen, T., Jensen, C., & Dyreson, C. (1999). Supporting Imprecision in Multidimensional Databases Using Granularities. Proceedings of the 11th International Conference on Scientific and Statistical Database Management (SSDBM'99), (pp. 90-101). Cleveland, USA.
30. Pei, J., Han, J., & Mao, R. (2000). CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemsets. Proceedings of the 5th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD'00), (pp. 21-30). Dallas, Texas.
31. Ross, K. S. (1997). Fast Computation of Sparse Datacubes. Proceedings of 23rd International Conference on Very Large Data Bases (VLDB'97), (pp. 116-125). Athens, Greece.
32. Shanmugasundaram, J., Fayyad, U., & Bradley, P. (1999). Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'99), (pp. 223-232).
33. Shoshani, A. (1997). OLAP and statistical databases: Similarities and differences. Proceedings of the 16th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS'99), (pp. 185-196). Tucson, USA.
34. Sismanis, Y., Deligiannakis, A., Roussopoulos, N., & Kotidis, Y. (2002). Dwarf: shrinking the petacube. Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data SIGMOD'02), (pp. 464-475). Madison, USA.
35. Stumme, G., Taouil, R., Bastide, Y., Pasquier, N., & Lakhal, L. (2002). Computing Iceberg Concept Lattices with Titanic. Data and Knowledge Engineering (DKE), 42 (2), 189-222.
36. Theodoratos, D., & Sellis, T. K. (1999). Designing data warehouses. Data and Knowledge Engineering, 31 (3), 279-301.
37. Theodoratos, D., & Xu, W. (2004). Constructing search spaces for materialized view selection. ACM 7th International Workshop on Data Warehousing and OLAP (DOLAP'04), (pp. 112-121). Washington, D.C., USA.
38. Vitter, J., & Wang, M. (1999). Approximate Computation of Multidimensional Aggregates of Sparse Data Using Wavelets. Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data (SIGMOD'99), (pp. 193- 204). Philadelphia, USA.
39. Wang, W., Lu, H., Feng, J., & Yu, J. (2002). Condensed Cube: An Effective Approach to Reducing Data Cube Size. Proceedings of the 18th International Conference on Data Engineering (ICDE'02), (pp. 213-222). San Jose, USA.
40. Xin, D., Shao, Z., Han, J., & Liu, H. (2006). Ccubing: Efficient computation of closed cubes by aggregation based checking. Proceedings of the 22nd International Conference on Data Engineering (ICDE'06), (p. 4). Atlanta, USA.
41. Zaki, M. J., & Hsio, C. (2002). CHARM: An Efficient Algorithm for Closed Itemset Mining. Proceedings of the Second SIAM International Conference on Data Mining (SDM'02). Arlington, USA.