Materials for Part 2: Data Cube and OLAP
The reading materials were selected to help
you form a basic understanding. In other words, those materials do not necessarily
represent the state-of-the-art of the area. If you are interested in frontier
research, it may be helpful to take a look on some major journals or conferences
related to data mining, such as:
Major journals in data mining: DMKD, TKDD, TKDE, KAIS
Major journals in machine learning: MLJ, JMLR
Major journals in database: TODS, VLDBJ
Major journals in information retrieval: TOIS, IP&M, IRJ
Major conferences in web search and mining: WWWJ, TOIT, TWeb
Major conferences in data mining: KDD, ICDM, SDM, ECMLPKDD, PAKDD
Major conferences in machine learning: ICML, NIPS, COLT
Major conferences in database: SIGMOD, VLDB, ICDE
Major conferences in information retrieval: SIGIR, CIKM
Major conferences in web search and mining: WWW, WSDM
Attn: The reading materials below are listed for the
course. Please do not duplicate
for commercial purposes without the permission of corresponding copyright holders.
J. Gray, S. Chaudhuri, A. Bosworth, A. Layman, D. Reichart, M. Venkatrao, F. Pellow, and H.
cube: A relational aggregation operator generalizing group-by, cross-tab,
and sub-totals. Data Mining and Knowledge Discovery, 1997, 1(1): 29-53.
V. Harinarayan, A. Rajaraman, and J. D.
Ullman. Implementing data cubes efficiently. In: Proceedings
of the 1996 ACM SIGMOD International Conference on Management of Data (SIGMOD'96), Montreal, Canada, 1996, 205-216.