Improved techniques for processing queries in full-text systems
SIGIR '87 Proceedings of the 10th annual international ACM SIGIR conference on Research and development in information retrieval
Data compression: methods and theory
Data compression: methods and theory
ACM Computing Surveys (CSUR)
Storing text retrieval systems on CD-ROM: compression and encryption considerations
ACM Transactions on Information Systems (TOIS)
ACM Computing Surveys (CSUR)
Using bitmaps for medium sized information retrieval systems
Information Processing and Management: an International Journal
Improved hierarchical bit-vector compression in document retrieval systems
Proceedings of the 9th annual international ACM SIGIR conference on Research and development in information retrieval
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
Signature files: an access method for documents and its analytical performance evaluation
ACM Transactions on Information Systems (TOIS)
Generative models for bitmap sets with compression applications: (extended abstract)
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Versioning a full-text information retrieval system
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Approximating shallow-light trees
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
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Bitmaps are data structures occurring often in information retrieval. They are useful; they are also large and expensive to store. For this reason, considerable effort has been devoted to finding techniques for compressing them. These techniques are most effective for sparse bitmaps. We propose a preprocessing stage, in which bitmaps are first clustered and the clusters used to transform their member bitmaps into sparser ones, that can be more effectively compressed. The clustering method efficiently generates a graph structure on the bitmaps. The results of applying our algorithm to the Bible is presented: for some sets of bitmaps, our method almost doubled the compression savings.