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Online Prediction of Semi-structured Data Streams and Its Application to XML Data Compression
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kawano, Shotaro Arimura, Hiroki Arikawa, Setsuo |
| Copyright Year | 2003 |
| Abstract | Discrete sequence prediction has a wide range of applications, e.g., sequence pattern discovery, anomaly detection, biological sequence analysis, data compression. This paper studies online prediction of XML data streams. We present a probabilistic prediction model for XML data streams, called XPST (XML Prediction Sux Tree), which is a natural generalization of variable-length context-based prediction model PST (Probabilistic sux tree) for semi-structured data streams. Then, we develop an ecient online prediction algorithm for XPST based on the online sux tree/trie construction technique. Finally, we show that the prediction and update time of this algorithm |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ieice.org/iss/de/DEWS/proc/2003/papers/6-C/6-C-01.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
