A Probabilistic XML Approach to Data Integration

Abstract

In mobile and ambient environments, devices need to become autonomous, managing and resolving problems without interference from a user. The database of a (mobile) device can be seen as its knowledge about objects in the 'real world'. Data exchange between small and/or large computing devices can be used to supplement and update this knowledge whenever a connection gets established. In many situations, however, data from different data sources referring to the same real world objects, may conflict. It is the task of the data management system of the device to resolve such conflicts without interference from a user. In this paper, we take a first step in the development of a probabilistic XML DBMS. The main idea is to drop the assumption that data in the database should be certain: subtrees in XML documents may denote possible views on the real world. We formally define the notion of probabilistic XML tree and several operations thereon. We also present an approach for determining a logical semantics for queries on probabilistic XML data. Finally, we introduce an approach for XML data integration where conflicts are resolved by the introduction of possibilities in the database.

Probabilistic XML: Models and Complexity

“…Despite the existence of techniques for compressing ProTDB documents [66], we lack a good understanding on when compression is possible and whether it is possible to obtain an optimal representation (with respect to compactness) of a px-space, in ProTDB and other models. A fundamental problem related to this one concerns equivalence of probabilistic XML documents: decide whether two representations define the same px-space [39]. As shown in [57], this problem admits a randomized polynomial-time decision procedure for PrXML {cie} when pdocuments are shallow, giving some hope of obtaining a more systematic procedure for minimizing the size of a p-document.…”

“…To represent the result of the integration, we need a way to capture the uncertainty in the schema mappings, in deduplication, or in resolving conflicting information. This uncertainty can be characterized by probabilistic mappings [26] and probabilistic data integration rules [38,39]. The outcome of the integration process can naturally be viewed as probabilistic XML (which is useful to query, update, and so on).…”

“…The direct translation of a set of possible worlds with probabilities into a PrXML {mux,ind} document, for instance, simply enumerates all possible worlds as children of a mux node and has the same size as the original space. The compression or simplification problem [39] is to obtain, given a probabilistic XML document, another more compact document that defines the same px-space.…”

A logical reasoning framework for modelling and merging uncertain semi-structured information

“…The framework has proved to be capable of modelling a variety of forms of uncertainty and has advantages over both approaches [6,10].…”

“…Two typical examples of integrating uncertainty into the XML structure are [6] and [10], both methods assign probabilistic values to elements in an XML document. A probability value can either be assigned to a leaf node (a textentry) or a tagname, but these two approaches offer different methods to calculate a final probability for a query of XML information.…”