@inproceedings{2e0ab4d7b1974c85a2b28ffe2f08241a,
title = "GRAMS3: An efficient framework for XML structural similarity search",
abstract = "Structural similarity search is a fundamental technology for XML data management. However, existing methods do not scale well with large volume of XML document. The pq-gram is an efficient way of extracting substructure from the tree-structured data for approximate structural similarity search. In this paper, we propose an effective framework GRAMS3 for evaluating structural similarity of XML data. First pq-grams of XML document are extracted; then we study the characteristics of pq-gram of XML and generate doc-gram vector using TGF-IGF model for XML tree; finally we employ locality sensitive hashing for efficiently structural similarity search of XML documents. An empirical study using both synthetic and real datasets demonstrates the framework is efficient.",
keywords = "Locality Sensitive Hashing, Structural Similarity, XML Document, pq-Gram",
author = "Peisen Yuan and Xiaoling Wang and Chaofeng Sha and Ming Gao and Aoying Zhou",
year = "2010",
doi = "10.1007/978-3-642-14589-6\_43",
language = "英语",
isbn = "3642145884",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "422--433",
booktitle = "Database Systems for Advanced Applications - 15th International Conference, DASFAA 2010, International Workshops",
note = "15th International Conference on Database Systems for Advanced Applications, DASFAA 2010 ; Conference date: 01-04-2010 Through 04-04-2010",
}