Treffer: Querying tree-structured data using dimension graphs

Title:
Querying tree-structured data using dimension graphs
Source:
Advanced information systems engineering (Porto, 13-17 June 2005)Lecture notes in computer science. :201-215
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 21 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Dept. of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, United States
School of Electr. and Comp. Engineering, National Techn. University of Athens, Athens, GR 15773, United States
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16895960
Database:
PASCAL Archive

Weitere Informationen

Tree structures provide a popular means to organize the information on the Web. Taxonomies of thematic categories, concept hierarchies, e-commerce product catalogs are examples of such structures. Querying multiple data sources that use tree structures to organize their data is a challenging issue due to name mismatches, structural differences and structural inconsistencies that occur in such structures, even for a single knowledge domain. In this paper, we present a method to query tree-structured data. We introduce dimensions which are sets of semantically related nodes in tree structures. Based on dimensions, we suggest dimension graphs. Dimension graphs can be automatically extracted from trees and abstract their structural information. They are semantically rich constructs that provide query guidance to pose and evaluate queries on trees. We design a query language to query tree-structured data. A key feature of this language is that queries are not restricted by the structure of the trees. We present a technique for evaluating queries and we provide necessary and sufficient conditions for checking query unsatisfiability. We also show how dimension graphs can be used to query multiple trees in the presence of structural differences and inconsistencies.