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STOC '95 Proceedings of the twenty-seventh annual ACM symposium on Theory of computing
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Journal of Computer and System Sciences
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SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
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Managing gigabytes (2nd ed.): compressing and indexing documents and images
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ACM Transactions on Information Systems (TOIS)
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Proceedings of the ninth international conference on Information and knowledge management
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Compression of inverted indexes For fast query evaluation
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
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ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
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COMPSAC '98 Proceedings of the 22nd International Computer Software and Applications Conference
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The VLDB Journal — The International Journal on Very Large Data Bases
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ICDE '05 Proceedings of the 21st International Conference on Data Engineering
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ACM Transactions on Database Systems (TODS)
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VLDB '06 Proceedings of the 32nd international conference on Very large data bases
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VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
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IEEE Transactions on Information Theory
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IEEE Transactions on Information Theory
HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
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Position list word aligned hybrid: optimizing space and performance for compressed bitmaps
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DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
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Information Systems
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In this paper we propose a technique of compressing bitmap indexes for application in data warehouses. This technique, called run-length Huffman (RLH), is based on run-length encoding and on Huffman encoding. Additionally, we present a variant of RLH, called RLH-N. In RLH-N a bitmap is divided into N-bit words that are compressed by RLH. RLH and RLH-N were implemented and experimentally compared to the well-known word aligned hybrid (WAH) bitmap compression technique that has been reported to provide the shortest query execution time. The experiments discussed in this paper show that: (1) RLH-compressed bitmaps are smaller than corresponding WAH-compressed bitmaps, regardless of the cardinality of an indexed attribute, (2) RLH-N-compressed bitmaps are smaller than corresponding WAH-compressed bitmaps for certain range of cardinalities of an indexed attribute, (3) RLH and RLH-N-compressed bitmaps offer shorter query response times than WAH-compressed bitmaps, for certain range of cardinalities of an indexed attribute, and (4) RLH-N assures shorter update time of compressed bitmaps than RLH.