Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics

Classical regular path queries (RPQs) can be too restrictive for some applications and answering such queries under approximate semantics to relax the query is desirable. While for answering regular path queries over graph databases under approximate semantics algorithms are available, such algorithms are scarce for the ontology-mediated setting. In this paper we extend an approach for answering RPQs over graph databases that uses weighted transducers to approximate paths from the query in two ways. The first extension is to answering approximate conjunctive 2-way regular path queries (C2RPQs) over graph databases and the second is to answering C2RPQs over ELH and DL-LiteR ontologies. We provide results on the computational complexity of the underlying reasoning problems and devise approximate query answering algorithms

Global Numerical Constraints on Trees

We introduce a logical foundation to reason on tree structures with constraints on the number of node occurrences. Related formalisms are limited to express occurrence constraints on particular tree regions, as for instance the children of a given node. By contrast, the logic introduced in the present work can concisely express numerical bounds on any region, descendants or ancestors for instance. We prove that the logic is decidable in single exponential time even if the numerical constraints are in binary form. We also illustrate the usage of the logic in the description of numerical constraints on multi-directional path queries on XML documents. Furthermore, numerical restrictions on regular languages (XML schemas) can also be concisely described by the logic. This implies a characterization of decidable counting extensions of XPath queries and XML schemas. Moreover, as the logic is closed under negation, it can thus be used as an optimal reasoning framework for testing emptiness, containment and equivalence

RDF Querying

Reactive Web systems, Web services, and Web-based publish/ subscribe systems communicate events as XML messages, and in many cases require composite event detection: it is not sufficient to react to single event messages, but events have to be considered in relation to other events that are received over time. Emphasizing language design and formal semantics, we describe the rule-based query language XChangeEQ for detecting composite events. XChangeEQ is designed to completely cover and integrate the four complementary querying dimensions: event data, event composition, temporal relationships, and event accumulation. Semantics are provided as model and fixpoint theories; while this is an established approach for rule languages, it has not been applied for event queries before

Assume-guarantee verification for probabilistic systems

We present a compositional verification technique for systems that exhibit both probabilistic and nondeterministic behaviour. We adopt an assume- guarantee approach to verification, where both the assumptions made about system components and the guarantees that they provide are regular safety properties, represented by finite automata. Unlike previous proposals for assume-guarantee reasoning about probabilistic systems, our approach does not require that components interact in a fully synchronous fashion. In addition, the compositional verification method is efficient and fully automated, based on a reduction to the problem of multi-objective probabilistic model checking. We present asymmetric and circular assume-guarantee rules, and show how they can be adapted to form quantitative queries, yielding lower and upper bounds on the actual probabilities that a property is satisfied. Our techniques have been implemented and applied to several large case studies, including instances where conventional probabilistic verification is infeasible

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

A Direct Translation from XPath to Nondeterministic Automata

Abstract. Since navigational aspects of XPath correspond to first-order definability, it has been proposed to use the analogy with the very successful technique of translating LTL into automata, and produce efficient translations of XPath queries into automata on unranked trees. These translations can then be used for a variety of reasoning tasks such as XPath consistency, or optimization, under XML schema constraints. In the verification scenarios, translations into both nondeterministic and alternating automata are used. But while a direct translation from XPath into alternating automata is known, only an indirect translation into nondeterministic automata- going via intermediate logics- exists. A direct translation is desirable as most XML specifications have particularly nice translations into nondeterministic automata and it is natural to use such automata to reason about XPath and schemas. The goal of the paper is to produce such a direct translation of XPath into nondeterministic automata.

vSPARQL: A View Definition Language for the Semantic Web

Translational medicine applications would like to leverage the biological and biomedical ontologies, vocabularies, and data sets available on the semantic web. We present a general solution for RDF information set reuse inspired by database views. Our view definition language, vSPARQL, allows applications to specify the exact content that they are interested in and how that content should be restructured or modified. Applications can access relevant content by querying against these view definitions. We evaluate the expressivity of our approach by defining views for practical use cases and comparing our view definition language to existing query languages

Reasoning about Independence in Probabilistic Models of Relational Data

We extend the theory of d-separation to cases in which data instances are not independent and identically distributed. We show that applying the rules of d-separation directly to the structure of probabilistic models of relational data inaccurately infers conditional independence. We introduce relational d-separation, a theory for deriving conditional independence facts from relational models. We provide a new representation, the abstract ground graph, that enables a sound, complete, and computationally efficient method for answering d-separation queries about relational models, and we present empirical results that demonstrate effectiveness.Comment: 61 pages, substantial revisions to formalisms, theory, and related wor