Combining structural and textual contexts for compressing semistructured databases

We describe a compression technique for semistructured documents, called SCMPPM, which combines the prediction by partial matching technique with structural contexts model (SCM) technique. SCMPPM takes advantage of the context information usually implicit in the structure of the text. The idea is to use a separate PPM model to compress the text that lies inside each different structure type (e.g., different XML tag). The intuition is that the distribution of the texts that belong to a given structure type should be similar, and different from that of other structure types. This should allow PPM to make better predictions. We test our idea against plain PPM modelling, as well as against other structure-aware techniques. Results show that the new compression method obtains significant improvements in compression ratios.