TY - GEN
T1 - Semantic querying of tree-structured data sources using partially specified tree patterns
AU - Theodoratos, Dimitri
AU - Dalamagas, Theodore
AU - Koufopoulos, Antonis
AU - Gehani, Narain
PY - 2005
Y1 - 2005
N2 - Nowadays, huge volumes of data are organized or exported in a tree-structured form. Querying capabilities are provided through queries that are based on branching path expression. Even for a single knowledge domain structural differences raise difficulties for querying data sources in a uniform way. In this paper, we present a method for semantically querying tree-structured data sources using partially specified tree patterns. Based on dimensions which are sets of semantically related nodes in tree structures, we define dimension graphs. Dimension graphs can be automatically extracted from trees and abstract their structural information. They are semantically rich constructs that support the formulation of queries and their efficient evaluation. We design a tree-pattern query language to query multiple tree-structured data sources. A central feature of this language is that the structure can be specified fully, partially, or not at all in the queries. Therefore, it can be used to query multiple trees with structural differences. We study the derivation of structural expressions in queries by introducing a set of inference rules for structural expressions. We define two types of query unsatisfiability and we provide necessary and sufficient conditions for checking each of them. Our approach is validated through experimental evaluation.
AB - Nowadays, huge volumes of data are organized or exported in a tree-structured form. Querying capabilities are provided through queries that are based on branching path expression. Even for a single knowledge domain structural differences raise difficulties for querying data sources in a uniform way. In this paper, we present a method for semantically querying tree-structured data sources using partially specified tree patterns. Based on dimensions which are sets of semantically related nodes in tree structures, we define dimension graphs. Dimension graphs can be automatically extracted from trees and abstract their structural information. They are semantically rich constructs that support the formulation of queries and their efficient evaluation. We design a tree-pattern query language to query multiple tree-structured data sources. A central feature of this language is that the structure can be specified fully, partially, or not at all in the queries. Therefore, it can be used to query multiple trees with structural differences. We study the derivation of structural expressions in queries by introducing a set of inference rules for structural expressions. We define two types of query unsatisfiability and we provide necessary and sufficient conditions for checking each of them. Our approach is validated through experimental evaluation.
KW - Query evaluation
KW - Query satisfiability
KW - Tree-pattern queries
KW - Tree-structured data
KW - XML
UR - http://www.scopus.com/inward/record.url?scp=33745793275&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745793275&partnerID=8YFLogxK
U2 - 10.1145/1099554.1099729
DO - 10.1145/1099554.1099729
M3 - Conference contribution
AN - SCOPUS:33745793275
SN - 1595931406
SN - 9781595931405
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 712
EP - 719
BT - CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
T2 - CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Y2 - 31 October 2005 through 5 November 2005
ER -