Heterogeneous XML Sources Research Articles

Structured content-aware discovery for improving XML data consistency

With the explosive growth of heterogeneous XML sources, data inconsistency has become a serious problem that leads to ineffective business operations and poor decision-making. To address such inconsistency, XML functional dependencies (XFDs) have been proposed to constrain the data integrity of a source. Unfortunately, existing approaches to XFDs have insufficiently addressed data inconsistency arising from both semantic and structural inconsistencies inherent in heterogeneous XML data sources. This paper proposes a novel approach, called SCAD, to discover anomalies from a given source, which is essential to address prevalent inconsistencies in XML data. Our contribution is twofold. First, we introduce a new type of path and value-based data constraint, called XML Conditional Structural Dependency (XCSD), whereby (i) the paths in XCSD approximately represent groups of similar paths in sources to express constraints on objects with diverse structures; while (ii) the values bound to particular elements express constraints with conditional semantics. XCSD can capture data inconsistency disregarded by XFDs.Second, our proposed SCAD is used to discover XCSDs from a given source. Our approach exploits the semantics of data structures to detect similar paths from the sources, from which a data summary is constructed as an input for the discovery process. This aims to avoid returning redundant data rules due to structural inconsistencies. During the discovery process, SCAD employs semantics hidden in the data values to discover XCSDs. To evaluate our proposed approach, experiments and case studies were conducted on synthetic datasets which contain structural diversity causing XML data inconsistency. The experimental results show that SCAD can discover more dependencies and the dependencies found convey more meaningful semantics than those of the existing XFDs.

XML document clustering: techniques and challenges

The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi-structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways. Different similarity measures have been extended and also in some context semantic issues have been taken into account. In this context, we review different XML clustering methods with considering different representation methods such as tree based and vector based with use of different similarity measures. We also propose taxonomy for these proposed methods.

Double-layered schema integration of heterogeneous XML sources

Schema integration aims to create a mediated schema as a unified representation of existing heterogeneous sources sharing a common application domain. These sources have been increasingly written in XML due to its versatility and expressive power. Unfortunately, these sources often use different elements and structures to express the same concepts and relations, thus causing substantial semantic and structural conflicts. Such a challenge impedes the creation of high-quality mediated schemas and has not been adequately addressed by existing integration methods. In this paper, we propose a novel method, named XINTOR, for automating the integration of heterogeneous schemas. Given a set of XML sources and a set of correspondences between the source schemas, our method aims to create a complete and minimal mediated schema: it completely captures all of the concepts and relations in the sources without duplication, provided that the concepts do not overlap. Our contributions are fourfold. First, we resolve structural conflicts inherent in the source schemas. Second, we introduce a new statistics-based measure, called path cohesion, for selecting concepts and relations to be a part of the mediated schema. The path cohesion is statistically computed based on multiple path quality dimensions such as average path length and path frequency. Third, we resolve semantic conflicts by augmenting the semantics of similar concepts with context-dependent information. Finally, we propose a novel double-layered mediated schema to retain a wider range of concepts and relations than existing mediated schemas, which are at best either complete or minimal, but not both. Performed on both real and synthetic datasets, our experimental results show that XINTOR outperforms existing methods with respect to (i) the mediated-schema quality using precision, recall, F-measure, and schema minimality; and (ii) the execution performance based on execution time and scale-up performance.

Retrieving XML data from heterogeneous sources through vague querying

We propose a framework for querying heterogeneous XML data sources. The framework ensures high autonomy to participating sources as it does not rely on a global schema or on semantic mappings between schemas. The basic intuition is that of extending traditional approaches for approximate query evaluation, by providing techniques for combining partial answers coming from different sources, possibly on the basis of limited knowledge about the local schemas (i.e., key constraints). We define a query language and its associated semantics, that allows us to collect as much information as possible from several heterogeneous XML sources. We provide algorithms for query evaluation and characterize the complexity of the query language. Finally, we validate the approach in a medical application scenario.

Combining Description Logics with synopses for inferring complex knowledge patterns from XML sources

This paper illustrates how a Description Logics fragment, combined with a specific data compression technique, can be used for inferring complex intensional knowledge patterns from a set of semantically heterogeneous XML sources. The paper first provides a detailed description of the various steps of our approach; then, it describes some experiments performed to test its accuracy; after this, it presents a wide range of applications possibly benefiting from inferred patterns; finally, it compares our approach with the related ones previously proposed in the literature.

A method for the unification of XML schemata

Extensible Markup Language (XML) is a common standard for data representation and exchange over the Web. Considering the increasing need for managing data on the Web, integration techniques are required to access heterogeneous XML sources. In this paper, we describe a unification method for heterogeneous XML schemata. The input to the unification method is a set of object-oriented-based canonical schemata that conceptually abstract local Document Type Definitions of the involved sources. The unification process applies specific algorithms and rules to the concepts of the canonical schemata to generate a preliminary ontology. Further adjustments on this preliminary ontology generate a reference ontology that acts as a front-end for user queries to the XML sources.