Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI: | http://purl.tuc.gr/dl/dias/12DCEC49-3FB5-4CFB-9587-A761D5EFB408 | ||
| Year | 2005 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
|
||
| Bibliographic Citation | M. Garofalakis and A. Kumar, "XML stream processing using tree-edit distance embeddings", ACM Trans. Dat. Syst., vol. 30, no. 1, pp. 279-332, Mar. 2005. doi:10.1145/1061318.1061326 https://doi.org/10.1145/1061318.1061326 | ||
| Appears in Collections |
We propose the first known solution to the problem of correlating, in small space, continuous streams of XML data through approximate (structure and content) matching, as defined by a general tree-edit distance metric. The key element of our solution is a novel algorithm for obliviously embedding tree-edit distance metrics into an L1 vector space while guaranteeing a (worst-case) upper bound of O(log2n log*n) on the distance distortion between any data trees with at most n nodes. We demonstrate how our embedding algorithm can be applied in conjunction with known random sketching techniques to (1) build a compact synopsis of a massive, streaming XML data tree that can be used as a concise surrogate for the full tree in approximate tree-edit distance computations; and (2) approximate the result of tree-edit-distance similarity joins over continuous XML document streams. Experimental results from an empirical study with both synthetic and real-life XML data trees validate our approach, demonstrating that the average-case behavior of our embedding techniques is much better than what would be predicted from our theoretical worst-case distortion bounds. To the best of our knowledge, these are the first algorithmic results on low-distortion embeddings for tree-edit distance metrics, and on correlating (e.g., through similarity joins) XML data in the streaming model.
Copyright © DIAS 2013
