Lore: a database management system for semistructured data
ACM SIGMOD Record
Comparative analysis of five XML query languages
ACM SIGMOD Record
XRel: a path-based approach to storage and retrieval of XML documents using relational databases
ACM Transactions on Internet Technology (TOIT)
XBase: making your gigabyte disk queriable
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
XML Data and Object Databases: A Perfect Couple?
Proceedings of the 17th International Conference on Data Engineering
DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Efficient Filtering of XML Documents for Selective Dissemination of Information
VLDB '00 Proceedings of the 26th 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
XMark: a benchmark for XML data management
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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Most query languages in XML database systems use Regular Path Expressions (RPE) to query or extract data from databases and some query processing and optimization techniques have been proposed for RPEs. Conceptually XML documents are collections of path instances. Each path instance should conform to an XML element tag sequence, called path schema. A RPE query can be written as an automaton that can represent a language, while path schemas can be seen as sentences. In this paper, a novel RPE computing approach, automaton match (AM), is proposed. AM queries the RPEs by matching the automatons with path schemas. The experimental results show AM is quite efficient for computing RPE queries.