Data on the Web: from relations to semistructured data and XML
Data on the Web: from relations to semistructured data and XML
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
APEX: an adaptive path index for XML data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Holistic twig joins: optimal XML pattern matching
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Index Structures for Path Expressions
ICDT '99 Proceedings of the 7th International Conference on Database Theory
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Indexing and Querying XML Data for Regular Path Expressions
Proceedings of the 27th International Conference on Very Large Data Bases
A Fast Index for Semistructured Data
Proceedings of the 27th International Conference on Very Large Data Bases
ViST: a dynamic index method for querying XML data by tree structures
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
PRIX: Indexing And Querying XML Using Prüfer Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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A new way of indexing XML document is proposed, which supports twig queries and queries with wildcards. An once-over index construction algorithm is also given. According to the Line Model we design, we consider XML document as a line, and every elements of the document as the line's segments. To query an XML document is to identify the corresponding segments. Using a range-based dynamic tree labeling scheme, each segment of the line is given a range. We put all the paths of XML document into a trie, and organize the range sets with B+-trees grouping by the nodes on the trie. Three operations are defined, which enable the range sets on the B+-trees corresponding to different nodes in the trie to operate with each other. The worst-case time complexity of the algorithm we designed for the operations is O(m+n). The final results of twig queries can be got through these operations directly at a speed similar to the simple path query. Through extensive experiments, we compare our method with other popular techniques. In particular, we show that the processing cost and disk I/O of our index method is linearly proportional to the complexity of query and the size of query results. Experimental results demostrate the great performance benefits of our proposed techniques.