Querying XML data is a well-explored topic thanks to powerful query languages such as XPath and XQuery. Both were designed to support the evaluation of binary predicates, which can be proven to be a limited approach to effective querying of XML data. In this paper, a fuzzy extension of the XPath query language is proposed. Its goal is to achieve more flexible querying through vague queries, which can be expressed exploiting fuzzy predicates and fuzzy connectives. We also provide an elegant definition of structure relaxation and primitive operators to span the space of relaxations. Finally we propose an approach to the fuzzy matching of XML trees: XPath provides a deep-equal function that can be used to assess whether two sequences are recursively equal. This can be restrictive, therefore we provide an extension named deep-similar to assess whether the sequences are similar both in content and in structure. We also provide the user with ranking functions to define how the results should be ranked and presented.

Fuzzy querying of semistructured data

SPOLETINI, PAOLA
2005-01-01

Abstract

Querying XML data is a well-explored topic thanks to powerful query languages such as XPath and XQuery. Both were designed to support the evaluation of binary predicates, which can be proven to be a limited approach to effective querying of XML data. In this paper, a fuzzy extension of the XPath query language is proposed. Its goal is to achieve more flexible querying through vague queries, which can be expressed exploiting fuzzy predicates and fuzzy connectives. We also provide an elegant definition of structure relaxation and primitive operators to span the space of relaxations. Finally we propose an approach to the fuzzy matching of XML trees: XPath provides a deep-equal function that can be used to assess whether two sequences are recursively equal. This can be restrictive, therefore we provide an extension named deep-similar to assess whether the sequences are similar both in content and in structure. We also provide the user with ranking functions to define how the results should be ranked and presented.
2005
9728924097
IADIS International Conference on Applied Computing
San Sebastian, Spagna
22-25 febbraio 2006
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/18689
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact