Approximation schemes for covering and packing problems in image processing and VLSI
Journal of the ACM (JACM)
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering to minimize the sum of cluster diameters
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
BIRCH: A New Data Clustering Algorithm and Its Applications
Data Mining and Knowledge Discovery
Approximation Algorithms for Clustering to Minimize the Sum of Diameters
SWAT '00 Proceedings of the 7th Scandinavian Workshop on Algorithm Theory
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Evaluating top-k queries over web-accessible databases
ACM Transactions on Database Systems (TODS)
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Algorithms for two-box covering
Proceedings of the twenty-second annual symposium on Computational geometry
DADA: a data cube for dominant relationship analysis
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Answering top-k queries with multi-dimensional selections: the ranking cube approach
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Efficient IR-style keyword search over relational databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
DataScope: viewing database contents in Google Maps' way
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
ARCube: supporting ranking aggregate queries in partially materialized data cubes
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
RankClus: integrating clustering with ranking for heterogeneous information network analysis
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Promotion analysis in multi-dimensional space
Proceedings of the VLDB Endowment
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The promotion analysis problem has been proposed in , where ranking-based promotion query processing techniques are studied to effectively and efficiently promote a given object, such as a product, by exploring ranked answers. To be more specific, in a multidimensional data set, our goal is to discover interesting subspaces in which the object is ranked high. In this paper, we extend the previously proposed promotion cube techniques and develop a cell clustering approach that is able to further achieve better tradeoff between offline materialization and online query processing. We formally formulate our problem and present a solution to it. Our empirical evaluation on both synthetic and real data sets show that the proposed technique can greatly speedup query processing with respect to baseline implementations.