XMill: an efficient compressor for XML data
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Introduction to algorithms
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
XPRESS: a queriable compression for XML data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Compressing XML with Multiplexed Hierarchical PPM Models
DCC '01 Proceedings of the Data Compression Conference
XGRIND: A Query-Friendly XML Compressor
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Comparative Analysis of XML Compression Technologies
World Wide Web
Evaluating the Role of Context in Syntax Directed Compression of XML Documents
DCC '06 Proceedings of the Data Compression Conference
Mobile shopping assistant: integration of mobile applications and web services
Proceedings of the 16th international conference on World Wide Web
Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments
Mobile shopping assistant: integration of mobile applications and web services
Proceedings of the 16th international conference on World Wide Web
EXEM: Efficient XML data exchange management for mobile applications
Information Systems Frontiers
Service-oriented architecture for mobile applications
Proceedings of the 1st international workshop on Software architectures and mobility
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As the number of mobile device users increases, the need for mobile business applications development increases as well. However, such development is impeded by the limited resources available on typical mobile phones. This paper presents a context-dependent XML compression approach that enables the deployment of business applications on mobile devices. That is, the compressed XML document is not self-contained and cannot be de-compressed without using information shared between the sender and the recipient. By relying on shared information, we obtain a better compression ratio than existing context-free compression algorithms.