Retrieval of Semistructured Web Data
Identifieur interne : 000084 ( France/Analysis ); précédent : 000083; suivant : 000085Retrieval of Semistructured Web Data
Auteurs : Elisa Bertino [Italie] ; Mohand-Saïd Hacid [France] ; Farouk Toumani [France]Source :
- Studies in Fuzziness and Soft Computing [ 1434-9922 ]
Abstract
Abstract: The ability to manage data whose structure is less rigid and strict than in conventional databases is important in many new application areas, such as biological databases, digital libraries, data integration and Web databases. Such data is called semistructured, since it cannot be constrained by a fixed predefined schema: the information that is normally associated with a schema is contained within the data, which is sometimes called self-describing. Such data has recently emerged as a particularly interesting research topic in which new data modelling and querying techniques are investigated. In this paper, we consider how constraint-based technology can be used to query and reason about semistructured data. The constraint system FT≤ [37] provides information ordering constraints interpreted over feature trees. Here, we show how a generalization of FT≤ combined with path constraints allows one to formally represent, state constraints, and reason about semistructured data. The constraint languages we propose provide possibilities to straightforwardly capture, for example, what it means for a tree to be a subtree or subsumed by another, or what it means for two paths to be divergent. We establish a logical semantics for our constraints thanks to axiom schemes presenting our first-order theory constraint system. We propose using the constraint systems for querying semistructured Web data.
Url:
DOI: 10.1007/978-3-7908-1772-0_19
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: The ability to manage data whose structure is less rigid and strict than in conventional databases is important in many new application areas, such as biological databases, digital libraries, data integration and Web databases. Such data is called semistructured, since it cannot be constrained by a fixed predefined schema: the information that is normally associated with a schema is contained within the data, which is sometimes called self-describing. Such data has recently emerged as a particularly interesting research topic in which new data modelling and querying techniques are investigated. In this paper, we consider how constraint-based technology can be used to query and reason about semistructured data. The constraint system FT≤ [37] provides information ordering constraints interpreted over feature trees. Here, we show how a generalization of FT≤ combined with path constraints allows one to formally represent, state constraints, and reason about semistructured data. The constraint languages we propose provide possibilities to straightforwardly capture, for example, what it means for a tree to be a subtree or subsumed by another, or what it means for two paths to be divergent. We establish a logical semantics for our constraints thanks to axiom schemes presenting our first-order theory constraint system. We propose using the constraint systems for querying semistructured Web data.</div>
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