Translation of relational queries into Description Logic for semantic cache query processing

Query containment is one of the building block of query optimization techniques. In the relational world, query containment is a well-studied problem. At the same time it is well-understood that relational queries are not enough to cope with graph-structured data, where one is interested in expressing queries that capture navigation in the graph. This paper contributes a study on the problem of query containment for an expressive class of navigational queries called Extended Property Paths (EPPs). EPPs are more expressive than previous navigational extension of SPARQL (e.g., nested regular expressions) as they allow to express path conjunction and path negation, among others. We attack the problem of EPPs containment and provide complexity bounds.

Revising knowledge bases (KBs) in description logics (DLs) in a syntax-independent manner is an important, nontrivial problem for the ontology management and DL communities. Several attempts have been made to adapt classical model-based belief revision and update techniques to DLs, but they are restricted in several ways. In particular, they do not provide operators or algorithms for general DL KB revision. The key difficulty is that, unlike propositional logic, a DL KB may have infinitely many models with complex (and possibly infinite) structures, making it difficult to define and compute revisions in terms of models. In this paper, we study general KBs in a specific DL in the DL-Lite family. We introduce the concept of features for such KBs, develop an alternative semantic characterization of KBs using features (instead of models), define two specific revision operators for KBs, and present the first algorithm for computing best approximations for syntax-independent revisions of KBs.

Solving the SPARQL query containment problem with SpeCS

Description logics (DLs) and rule-based systems are two prominent families of knowledge representation formalisms. While DLs are focused on describing and reasoning about conceptual knowledge, rules are focused on answering queries about facts in the knowledge base. So far, research on DLs has been largely isolated from the research on rules. With the advent of the Semantic Web, however, it became apparent that neither formalism alone can cover all the practical use cases. The integration between DLs and rules, however, is technically challenging due to significant differences in the underlying semantic assumptions. In particular, DLs are based on standard first-order semantics and open-world assumption, whereas rules typically employ closed-world semantics based on a variant of circumscription. In my talk, I shall present an overview of the benefits of integrating DLs and rules in a coherent semantic framework, and shall discuss the main challenges in achieving a tight integration. I shall present an overview of the approaches currently discussed in literature. Finally, I shall present in more detail the approach that is based on the nonmonotonic logic MKNF by Lifschitz. This approach is tight in the sense that DLs and rules are given a common model-theoretic semantics. Furthermore, it is faithful in the sense that it is compatible with the original semantics of both DLs and rules. Finally, it is expressive and can naturally capture many of the existing proposals. I shall discuss the definitions of the semantics of the hybrid formalism, present a decision procedure for a particular decidable fragment, and discuss the complexity bounds of reasoning.

Answering regular path queries in expressive Description Logics via alternating tree-automata

article Free Access Share on Containment of conjunctive queries: beyond relations as sets Authors: Yannis E. Ioannidis Univ. of Wisconsin, Madison Univ. of Wisconsin, MadisonView Profile , Raghu Ramakrishnan View Profile Authors Info & Claims ACM Transactions on Database SystemsVolume 20Issue 3Sept. 1995 pp 288–324https://doi.org/10.1145/211414.211419Published:01 September 1995Publication History 89citation759DownloadsMetricsTotal Citations89Total Downloads759Last 12 Months36Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

A query under an object-oriented data model exhibits characteristics which one finds in a relational query and those which clearly separate it from a relational query. The differences in turn have interesting impacts on the complexity of and strategy for query evaluation in object-oriented databases. The authors develop a model of a query under an object-oriented data model, and analyze the fundamental differences in the semantics of queries in object-oriented databases and relational databases. >

For designing Entity-relationship(ER) schemas, an interesting topic is how to transform ER schemas into knowledge bases (KBs) in description logics (DLs). It is significance in translations that one can use automated DL reasoning services to support the development and maintenance of correct ER schemas. This paper proposed a faithful translation, which translates ER schemas into KBs in the description logic ALDL and allows us to reduce reasoning on ER schemas to finite models reasoning on ALDL KBs.

This paper addresses the problem of relational queries processing in the domain based database machine DBMAC. A brief description of the storage organisation of the domain based DBMS is first given. Then the operating principles of the domain based data-model, called D-model, is described through some examples. The central part of the paper deals with the translation of relational queries into operations on objects of the D-model. Objects of the D-model and a set of operations on these objects are first defined : this set S of operations is shown to be complete in that any relational query can be translated into D-model operations belonging to S.Finally we give a method for processing relation queries using D-model operations.The basic advantages to be expected from a domain based physical organization of data are :1. fast equi-join execution,2. a compact representation of intermediate results.The latter should lead to efficient processing of complex queries, provided a powerful parallel physical architecture is chosen for implementation.

An important issue that arises when querying description logic (DL) knowledge bases is how to handle the case in which the knowledge base is inconsistent. Indeed, while it may be reasonable to assume that the TBox (ontology) has been properly debugged, the ABox (data) will typically be very large and subject to frequent modifications, both of which make errors likely. As standard DL semantics is useless in such circumstances (everything is entailed from a contradiction), several alternative inconsistency-tolerant semantics have been proposed with the aim of providing meaningful answers to queries in the presence of such data inconsistencies. In the first part of this chapter, we present and compare these inconsistency-tolerant semantics, which can be applied to any DL (or ontology language). The second half of the chapter summarizes what is known about the computational properties of these semantics and gives an overview of the main algorithmic techniques and existing systems, focusing on DLs of the DL-Lite family.

Conjunctive regular path queries are an expressive extension of the well-known class of conjunctive queries. Such queries have been extensively studied in the (graph) database community, since they support a controlled form of recursion and enable sophisticated path navigation. Somewhat surprisingly, there has been little work aimed at using such queries in the context of description logic (DL) knowledge bases, particularly for the lightweight DLs that are considered best suited for data-intensive applications. This paper aims to bridge this gap by providing algorithms and tight complexity bounds for answering two-way conjunctive regular path queries over DL knowledge bases formulated in lightweight DLs of the DL-Lite and EL families. Our results demonstrate that in data complexity, the cost of moving to this richer query language is as low as one could wish for: the problem is NL-complete for DL-Lite and P-complete for EL. The combined complexity of query answering increases from NP- to PSpace-complete, but for two-way regular path queries (without conjunction), we show that query answering is tractable even with respect to combined complexity. Our results reveal two-way conjunctive regular path queries as a promising language for querying data enriched by ontologies formulated in DLs of the DL-Lite and EL families or the corresponding OWL 2 QL and EL profiles.

The past 25 years have seen many attempts to introduce defeasible-reasoning capabilities into a description logic setting. Many, if not most, of these attempts are based on preferential extensions of description logics, with a significant number of these, in turn, following the so-called KLM approach to defeasible reasoning initially advocated for propositional logic by Kraus, Lehmann, and Magidor. Each of these attempts has its own aim of investigating particular constructions and variants of the (KLM-style) preferential approach. Here our aim is to provide a comprehensive study of the formal foundations of preferential defeasible reasoning for description logics in the KLM tradition.We start by investigating a notion ofdefeasible subsumptionin the spirit of defeasible conditionals as studied by Kraus, Lehmann, and Magidor in the propositional case. In particular, we consider a natural and intuitive semantics for defeasible subsumption, and we investigate KLM-style syntactic properties for bothpreferentialandrationalsubsumption. Our contribution includes two representation results linking our semantic constructions to the set of preferential and rational properties considered. Besides showing that our semantics is appropriate, these results pave the way for more effective decision procedures for defeasible reasoning in description logics. Indeed, we also analyse the problem of non-monotonic reasoning in description logics at the level ofentailmentand present an algorithm for the computation ofrational closureof a defeasible knowledge base. Importantly, our algorithm relies completely on classical entailment and shows that the computational complexity of reasoning over defeasible knowledge bases is no worse than that of reasoning in the underlying classical DLALC.

Similarity-based relaxed instance queries

This chapter provides an overview of the four prototypical systems that either implement the SPS reference architecture or were built on top of the SPS reference architecture. All four systems, namely ArbiterOne, eVoces, EscapeMisery, and SpotCrowd have a very different application domain, which provides strong evidence for the SPS and the S-PDL being truly applicable across a vast variety of domains. The second part of this chapter provides insights into system qualityrelated aspects. Thereby, the focus is put upon the assurance of real-time performance of semantic search query processing. Based on the formal measurement process definition in section 4.4, the results of two measurements projects, which were carried out on the ArbiterOne system, are presented and interpreted.

Non expert users need support to access linked data available on the Web. To this aim, keyword-based search is considered an essential feature of database systems. The distributed nature of the Semantic Web demands query processing techniques to evolve towards a scenario where data is scattered on distributed data stores. Existing approaches to keyword search cannot guarantee scalability in a distributed environment, because, at runtime, they are unaware of the location of the relevant data to the query and thus, they cannot optimize join tasks. In this paper, we illustrate a novel distributed approach to keyword search over RDF data that exploits the MapReduce paradigm by switching the problem from graph-parallel to data-parallel processing. Moreover, our framework is able to consider ranking during the building phase to return directly the best (top-k) answers in the first (k) generated results, reducing greatly the overall computational load and complexity. Finally, a comprehensive evaluation demonstrates that our approach exhibits very good efficiency guaranteeing high level of accuracy, especially with respect to state-of-the-art competitors.Keywords#eswc2014Virgilio