With the tremendous growth of World Wide Web
(WWW) data, there is an emerging need for effective information
retrieval at the document level. Several query languages such as
XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent
years to provide faster way of querying XML data, but they still lack of
generality and efficiency. Our approach towards evolving a framework
for querying semistructured documents is based on formal query
algebra. Two elements are introduced in the proposed framework:
first, a generic and flexible data model for logical representation of
semistructured data and second, a set of operators for the manipulation
of objects defined in the data model. In additional to accommodating
several peculiarities of semistructured data, our model offers novel
features such as bidirectional paths for navigational querying and
partitions for data transformation that are not available in other
proposals.
[1] S. Abiteboul, D. Quass, J. Mchugh, J. Widom, J. Wiener. The Lorel Query
Language for Semistructured Data. Journal of Digital Libraries, l(l):68-88,
April 1997..
[2] J. Mchugh, S. Abiteboul, R. Goldman, D. Quass, J. Widom. Lore: A
Database Management System for Semistructured Data. SIGMOD
Record, 26(3):54-66, September 1997.H. Poor, An Introduction to Signal
Detection and Estimation. New York: Springer-Verlag, 1985, ch. 4.
[3] D. Quass, A. Rajaraman, Y. Sagiv, J. Ullman, J. Widom. Querying
Semistructured Heterogeneous Information. Journal of Systems
Integration, pp. 7(3/4):381-407, September 1997.
[4] World Wide Web Consortium. Document Object Model (DOM) Level 1
Specification. http://www. w3. org/TR/REC-DOM-Level-1.
[5] World Wide Web Consortium. Extensible Markup Language (XML) 1.0,
1998. http://www. w3. org/TR/REC-xml.
[6] vidmar
[1] S. Abiteboul, D. Quass, J. Mchugh, J. Widom, J. Wiener. The Lorel Query
Language for Semistructured Data. Journal of Digital Libraries, l(l):68-88,
April 1997..
[2] J. Mchugh, S. Abiteboul, R. Goldman, D. Quass, J. Widom. Lore: A
Database Management System for Semistructured Data. SIGMOD
Record, 26(3):54-66, September 1997.H. Poor, An Introduction to Signal
Detection and Estimation. New York: Springer-Verlag, 1985, ch. 4.
[3] D. Quass, A. Rajaraman, Y. Sagiv, J. Ullman, J. Widom. Querying
Semistructured Heterogeneous Information. Journal of Systems
Integration, pp. 7(3/4):381-407, September 1997.
[4] World Wide Web Consortium. Document Object Model (DOM) Level 1
Specification. http://www. w3. org/TR/REC-DOM-Level-1.
[5] World Wide Web Consortium. Extensible Markup Language (XML) 1.0,
1998. http://www. w3. org/TR/REC-xml.
[6] vidmar
@article{"International Journal of Information, Control and Computer Sciences:61553", author = "Ei Ei Myat and Ni Lar Thein", title = "Query Algebra for Semistuctured Data", abstract = "With the tremendous growth of World Wide Web
(WWW) data, there is an emerging need for effective information
retrieval at the document level. Several query languages such as
XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent
years to provide faster way of querying XML data, but they still lack of
generality and efficiency. Our approach towards evolving a framework
for querying semistructured documents is based on formal query
algebra. Two elements are introduced in the proposed framework:
first, a generic and flexible data model for logical representation of
semistructured data and second, a set of operators for the manipulation
of objects defined in the data model. In additional to accommodating
several peculiarities of semistructured data, our model offers novel
features such as bidirectional paths for navigational querying and
partitions for data transformation that are not available in other
proposals.", keywords = "Algebra, Semistructured data, Query Algebra.", volume = "2", number = "10", pages = "3547-4", }