Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
A technique for counting ones in a binary computer
Communications of the ACM
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Design of the Java HotSpot™ client compiler for Java 6
ACM Transactions on Architecture and Code Optimization (TACO)
Optimizing Frequency Queries for Data Mining Applications
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Analyses of multi-level and multi-component compressed bitmap indexes
ACM Transactions on Database Systems (TODS)
Position list word aligned hybrid: optimizing space and performance for compressed bitmaps
Proceedings of the 13th International Conference on Extending Database Technology
SPARQL query answering with bitmap indexes
SWIM '12 Proceedings of the 4th International Workshop on Semantic Web Information Management
Minimizing index size by reordering rows and columns
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Polygon-Based Query Evaluation over Geospatial Data Using Distributed Hash Tables
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Bit arrays, or bitmaps, are used to significantly speed up set operations in several areas, such as data warehousing, information retrieval, and data mining, to cite a few. However, bitmaps usually use a large storage space, thus requiring compression. Consequently, there is a space-time tradeoff among compression schemes. The Word Aligned Hybrid (WAH) bitmap compression trades some space to allow for bitwise operations without first decompressing bitmaps. WAH has been recognized as the most efficient scheme in terms of computation time. In this paper we present Concise (Compressed 'n' Composable Integer Set), a new scheme that enjoys significantly better performances than WAH. In particular, when compared to WAH our algorithm is able to reduce the required memory up to 50%, while having comparable computation time. Further, we show that Concise can be efficiently used to represent sets of integral numbers in lieu of well-known data structures such as arrays, lists, hashtables, and self-balancing binary search trees. Extensive experiments over synthetic data show the effectiveness of our proposal.