Comparative Analysis of XML Compression Technologies
World Wide Web
A compressor for effective archiving, retrieval, and updating of XML documents
ACM Transactions on Internet Technology (TOIT)
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
XML compression techniques: A survey and comparison
Journal of Computer and System Sciences
Proceedings of the 24th ACM SIGPLAN conference companion on Object oriented programming systems languages and applications
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Feasibility study of software reengineering towards role-based access control
International Journal of Computer Applications in Technology
A feature-oriented approach to platform-specific modelling of coarse-grained components
International Journal of Computer Applications in Technology
International Journal of Computer Applications in Technology
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Usually, storage performance of data provenance is sustained through the use of compression algorithms. When provenance models with high repeatable rate and small variances are concerned, many current algorithms still face the challenge of avoiding redundancy. Adaptive Merge algorithm, featuring the optimisation of provenance factorisation, is introduced to compress provenance tree on the self-adaptive granularity basis. A kind of comprehensive solution regarding pointer-saving storage is provided here. The validity of Adaptive Merge algorithm is proven experimentally. Comparisons are made with Argument Factorisation to prove that our algorithm performs better in compression ratio. The extent of ratio enhancement depends on the features of data sets. The compression ratio of the provided provenance data set is increased by about 10%. Other data sets all show improvements in varying degrees. This suggests that by resolving pointer explosion issue, this new algorithm performs better and achieves a more reasonable compression ratio.