Novel techniques for data warehousing and online analytical processing in emerging applications
暂无分享,去创建一个
Jian Pei | Xin He | Moonjung Cho | J. Pei | Xin He | M. Cho | Moonjung Cho
[1] Rajeev Motwani,et al. Computing Iceberg Queries Efficiently , 1998, VLDB.
[2] Mohammed J. Zaki,et al. TRICLUSTER: an effective algorithm for mining coherent clusters in 3D microarray data , 2005, SIGMOD '05.
[3] Jennifer Widom,et al. Models and issues in data stream systems , 2002, PODS.
[4] Jeffrey Scott Vitter,et al. Data cube approximation and histograms via wavelets , 1998, CIKM '98.
[5] Raymond T. Ng,et al. Iceberg-cube computation with PC clusters , 2001, SIGMOD '01.
[6] Surajit Chaudhuri,et al. An overview of data warehousing and OLAP technology , 1997, SGMD.
[7] Sunita Sarawagi. Indexing OLAP Data , 1997, IEEE Data Eng. Bull..
[8] Jian Pei,et al. Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach , 2006, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06).
[9] Jian Pei,et al. Mining coherent gene clusters from gene-sample-time microarray data , 2004, KDD.
[10] Jiawei Han,et al. Pushing aggregate constraints by divide-and-approximate , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).
[11] Rajeev Rastogi,et al. Processing complex aggregate queries over data streams , 2002, SIGMOD '02.
[12] Wei Wang,et al. OP-cluster: clustering by tendency in high dimensional space , 2003, Third IEEE International Conference on Data Mining.
[13] Srinivasan Parthasarathy,et al. New Algorithms for Fast Discovery of Association Rules , 1997, KDD.
[14] Richard M. Karp,et al. A simple algorithm for finding frequent elements in streams and bags , 2003, TODS.
[15] Jennifer Widom,et al. Research problems in data warehousing , 1995, CIKM '95.
[16] Divyakant Agrawal,et al. Range cube: efficient cube computation by exploiting data correlation , 2004, Proceedings. 20th International Conference on Data Engineering.
[17] Philip S. Yu,et al. Clustering by pattern similarity in large data sets , 2002, SIGMOD '02.
[18] V. S. Subrahmanian,et al. Maintaining views incrementally , 1993, SIGMOD Conference.
[19] Hongjun Lu,et al. False Positive or False Negative: Mining Frequent Itemsets from High Speed Transactional Data Streams , 2004, VLDB.
[20] Yixin Chen,et al. Multi-Dimensional Regression Analysis of Time-Series Data Streams , 2002, VLDB.
[21] Graham Cormode,et al. What's hot and what's not: tracking most frequent items dynamically , 2003, PODS '03.
[22] Xintao Wu,et al. Using Loglinear Models to Compress Datacube , 2000, Web-Age Information Management.
[23] Yannis Sismanis,et al. Dwarf: shrinking the PetaCube , 2002, SIGMOD '02.
[24] Piotr Indyk,et al. Maintaining Stream Statistics over Sliding Windows , 2002, SIAM J. Comput..
[25] Philip S. Yu,et al. Mining Frequent Patterns in Data Streams at Multiple Time Granularities , 2002 .
[26] Ralph Arnote,et al. Hong Kong (China) , 1996, OECD/G20 Base Erosion and Profit Shifting Project.
[27] Jennifer Widom,et al. On-line warehouse view maintenance , 1997, SIGMOD '97.
[28] Kenneth A. Ross,et al. Fast Computation of Sparse Datacubes , 1997, VLDB.
[29] Won Suk Lee,et al. Finding recent frequent itemsets adaptively over online data streams , 2003, KDD '03.
[30] Gurmeet Singh Manku,et al. Approximate counts and quantiles over sliding windows , 2004, PODS.
[31] Charu C. Aggarwal,et al. A Tree Projection Algorithm for Generation of Frequent Item Sets , 2001, J. Parallel Distributed Comput..
[32] Divesh Srivastava,et al. On computing correlated aggregates over continual data streams , 2001, SIGMOD '01.
[33] Werner Nutt,et al. Rewriting aggregate queries using views , 1999, PODS.
[34] Jian Pei,et al. DHC: a density-based hierarchical clustering method for time series gene expression data , 2003, Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings..
[35] Inderpal Singh Mumick,et al. Maintenance of data cubes and summary tables in a warehouse , 1997, SIGMOD '97.
[36] Laks V. S. Lakshmanan,et al. QC-trees: an efficient summary structure for semantic OLAP , 2003, SIGMOD '03.
[37] Jennifer Widom,et al. Continuous queries over data streams , 2001, SGMD.
[38] Laks V. S. Lakshmanan,et al. Quotient Cube: How to Summarize the Semantics of a Data Cube , 2002, VLDB.
[39] Philip S. Yu,et al. Finding generalized projected clusters in high dimensional spaces , 2000, SIGMOD '00.
[40] George M. Church,et al. Biclustering of Expression Data , 2000, ISMB.
[41] Raghu Ramakrishnan,et al. Bottom-up computation of sparse and Iceberg CUBE , 1999, SIGMOD '99.
[42] Setsuo Ohsuga,et al. INTERNATIONAL CONFERENCE ON VERY LARGE DATA BASES , 1977 .
[43] Hongjun Lu,et al. Condensed cube: an effective approach to reducing data cube size , 2002, Proceedings 18th International Conference on Data Engineering.
[44] Graham Cormode,et al. What's hot and what's not: tracking most frequent items dynamically , 2003, TODS.
[45] Dimitrios Gunopulos,et al. Automatic subspace clustering of high dimensional data for data mining applications , 1998, SIGMOD '98.
[46] H. V. Jagadish,et al. Semantic Compression and Pattern Extraction with Fascicles , 1999, VLDB.
[47] Jian Pei,et al. Efficient computation of Iceberg cubes with complex measures , 2001, SIGMOD '01.
[48] Philip S. Yu,et al. /spl delta/-clusters: capturing subspace correlation in a large data set , 2002, Proceedings 18th International Conference on Data Engineering.
[49] Divesh Srivastava,et al. Answering Queries with Aggregation Using Views , 1996, VLDB.
[50] Guizhen Yang,et al. The complexity of mining maximal frequent itemsets and maximal frequent patterns , 2004, KDD.
[51] Hamid Pirahesh,et al. Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals , 1996, Data Mining and Knowledge Discovery.
[52] Jennifer Widom,et al. Making views self-maintainable for data warehousing , 1996, Fourth International Conference on Parallel and Distributed Information Systems.
[53] Philip S. Yu,et al. A Regression-Based Temporal Pattern Mining Scheme for Data Streams , 2003, VLDB.
[54] Divesh Srivastava,et al. Finding Hierarchical Heavy Hitters in Data Streams , 2003, VLDB.
[55] Kenneth A. Ross,et al. Optimizing selections over datacubes , 2000, Proceedings. 12th International Conference on Scientific and Statistica Database Management.
[56] Nicolas Pasquier,et al. Discovering Frequent Closed Itemsets for Association Rules , 1999, ICDT.
[57] Nick Roussopoulos,et al. Cubetree: Organization of and Bulk Updates on the Data Cube , 1997, SIGMOD Conference.
[58] Philip S. Yu,et al. MaPle: a fast algorithm for maximal pattern-based clustering , 2003, Third IEEE International Conference on Data Mining.
[59] Mark Sullivan,et al. Quasi-cubes: exploiting approximations in multidimensional databases , 1997, SGMD.
[60] C. J. Hahn,et al. Extended Edited Synoptic Cloud Reports from Ships and Land Stations Over the Globe, 1952-1996 , 1999 .
[61] Stephen G. Warren,et al. Edited synoptic cloud reports from ships and land stations over the globe , 1996 .
[62] Alberto O. Mendelzon,et al. Temporal Queries in OLAP , 2000, VLDB.
[63] Philip S. Yu,et al. Fast algorithms for projected clustering , 1999, SIGMOD '99.
[64] Jeffrey F. Naughton,et al. An array-based algorithm for simultaneous multidimensional aggregates , 1997, SIGMOD '97.
[65] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[66] Jonathan Goldstein,et al. When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.
[67] Stephen R. Gardner. Building the data warehouse , 1998, CACM.
[68] Paul S. Bradley,et al. Compressed data cubes for OLAP aggregate query approximation on continuous dimensions , 1999, KDD '99.
[69] Yi Zhang,et al. Entropy-based subspace clustering for mining numerical data , 1999, KDD '99.
[70] Jeffrey D. Ullman,et al. Implementing data cubes efficiently , 1996, SIGMOD '96.
[71] Bernhard Ganter,et al. Formal Concept Analysis: Mathematical Foundations , 1998 .
[72] Rakesh Agarwal,et al. Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.
[73] Jiawei Han,et al. Star-Cubing: Computing Iceberg Cubes by Top-Down and Bottom-Up Integration , 2003, Very Large Data Bases Conference.
[74] RamakrishnanRaghu,et al. Bottom-up computation of sparse and Iceberg CUBE , 1999 .