XRel: a path-based approach to storage and retrieval of XML documents using relational databases
ACM Transactions on Internet Technology (TOIT)
APEX: an adaptive path index for XML data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Storing and querying ordered XML using a relational database system
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Relational Databases for Querying XML Documents: Limitations and Opportunities
VLDB '99 Proceedings of the 25th 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
Developing an Indexing Scheme for XML Document Collection using the Oracle8i Extensibility Framework
Proceedings of the 27th International Conference on Very Large Data Bases
Indexing XML data stored in a relational database
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
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We propose an improved approach that stores and queries a large volume of XML documents in a relational database, while removing the redundancy of path information and using an inverted index on the reduced path information. In order to store XML documents in a relational database, the XML document is decomposed into nodes based on its tree structure, and stored in relational tables with path information from the root node to each node. The existing XML storage methods which use relational data model, usually store path information for every node. Thus, they can increase storage overhead and decrease query processing performance with the increased data volume. Our approach stores only leaf node path information in XML tree structure while finding out internal node path information from the leaf node path information. In this manner, our approach can reduce data volume for a large amount of XML documents to a degree and also reduce the size of inverted index for the path information with the smaller number of posting lists by key words. We show the effectiveness of this approach through several experiments that compare XPath query performance with the existing methods.