On the Top-k Retrieval Problem for Ontology-Based Access to Databases

Straccia, Umberto

doi:10.1007/978-3-319-00954-4_5

Cited by 8 publications

(9 citation statements)

References 52 publications

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“…queries. The most related work is the one presented by Straccia [45] which considers the problem of evaluating top-k queries in the context of OBDA over relational databases.…”

Section: State Of the Artmentioning

confidence: 99%

Handling qualitative preferences in SPARQL over virtual ontology-based data access

Gonçalves

Chaves-Fraga

Corcho

2022

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With the increase of data volume in heterogeneous datasets that are being published following Open Data initiatives, new operators are necessary to help users to find the subset of data that best satisfies their preference criteria. Quantitative approaches such as top-k queries may not be the most appropriate approaches as they require the user to assign weights that may not be known beforehand to a scoring function. Unlike the quantitative approach, under the qualitative approach, which includes the well-known skyline, preference criteria are more intuitive in certain cases and can be expressed more naturally. In this paper, we address the problem of evaluating SPARQL qualitative preference queries over an Ontology-Based Data Access (OBDA) approach, which provides uniform access over multiple and heterogeneous data sources. Our main contribution is Morph-Skyline++, a framework for processing SPARQL qualitative preferences by directly querying relational databases. Our framework implements a technique that translates SPARQL qualitative preference queries directly into queries that can be evaluated by a relational database management system. We evaluate our approach over different scenarios, reporting the effects of data distribution, data size, and query complexity on the performance of our proposed technique in comparison with state-of-the-art techniques. Obtained results suggest that the execution time can be reduced by up to two orders of magnitude in comparison to current techniques scaling up to larger datasets while identifying precisely the result set.

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“…queries. The most related work is the one presented by Straccia [45] which considers the problem of evaluating top-k queries in the context of OBDA over relational databases.…”

Section: State Of the Artmentioning

confidence: 99%

Handling qualitative preferences in SPARQL over virtual ontology-based data access

Gonçalves

Chaves-Fraga

Corcho

2022

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“…ontologies is an important extension of the classical problem of CQ answering in databases, which has recently received considerable attention [8,47]. For FDLs, several fuzzy extensions of CQs have been proposed [48,56,57]. In [21,43], we have extended the crispification approach to answer fuzzy CQs in finitely valued FDLs.…”

Section: Finitely Valued Fdlsmentioning

confidence: 99%

Decidability and Complexity of Fuzzy Description Logics

2016

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Fuzzy description logics (FDLs) have been introduced to represent concepts for which membership cannot be determined in a precise way, i.e., where instead of providing a strict border between being a member and not being a member, it is more appropriate to model a gradual change from membership to nonmembership. First approaches for reasoning in FDLs where based either on a reduction to reasoning in classical description logics (DLs) or on adaptations of reasoning approaches for DLs to the fuzzy case. However, it turned out that these approaches in general do not work if expressive terminological axioms, called general concept inclusions (GCIs), are available in the FDL. The goal of this project was a comprehensive study of the border between decidability and undecidability for FDLs with GCIs, as well as determining the exact complexity of the decidable logics. As a result, we have provided an almost complete classification of the decidability and complexity of FDLs with GCIs. Keywords Knowledge Representation and Reasoning • Vagueness • Fuzzy Description Logics 1 Introduction Fuzzy description logics have been studied for over two decades, with the aim of providing logic-based knowledge representation and reasoning algorithms capable Supported by DFG under grant BA 1122/17-1.

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“…Such kind of queries have already been defined in the literature [19,26,27] and the question is if the reduction technique can be applied to answer them. By taking account the fact that the reduction technique works on finite valued fuzzy DLs, these problems can be solved by considering for all possible combinations of degrees in [0, 1] O .…”

Section: Generalizing the Query Componentmentioning

confidence: 99%

“…Another interesting problem, specific to fuzzy DLs, is the top-k query answering problem presented in [25,26,27]. This variation of the fuzzy query answering problem focuses on the k answers with the highest degrees of satisfaction.…”

Section: Generalizing the Query Componentmentioning

confidence: 99%

Conjunctive Query Answering in Finitely-Valued Fuzzy Description Logics

Mailis

Peñaloza

Turhan

2014

Web Reasoning and Rule Systems

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Fuzzy Description Logics (DLs) generalize crisp ones by providing membership degree semantics for concepts and roles. A popular technique for reasoning in fuzzy DL ontologies is by providing a reduction to crisp DLs and then employ reasoning in the crisp DL. In this paper we adopt this approach to solve conjunctive query (CQ) answering problems for fuzzy DLs. We give reductions for Gödel, and Łukasiewicz variants of fuzzy SROIQ and two kinds of fuzzy CQs. The correctness of the proposed reduction is proved and its complexity is studied for different fuzzy variants of SROIQ.

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On the Top-k Retrieval Problem for Ontology-Based Access to Databases

Cited by 8 publications

References 52 publications

Handling qualitative preferences in SPARQL over virtual ontology-based data access

Handling qualitative preferences in SPARQL over virtual ontology-based data access

Decidability and Complexity of Fuzzy Description Logics

Conjunctive Query Answering in Finitely-Valued Fuzzy Description Logics

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