scholarly journals Temporal Query Answering in DL-Lite with Negation

10.29007/2df8 ◽  
2018 ◽  
Author(s):  
Stefan Borgwardt ◽  
Veronika Thost
Keyword(s):  
Temporal Logic ◽  
Domain Knowledge ◽  
Relational Databases ◽  
Query Language ◽  
Description Logics ◽  
Query Answering ◽  
Open World ◽  
Temporal Query ◽  
Temporal Query Language ◽  
Open World Assumption

Ontology-based query answering augments classical query answering in databases by adopting the open-world assumption and by including domain knowledge provided by an ontology. We investigate temporal query answering w.r.t. ontologies formulated in DL-Lite, a family of description logics that captures the conceptual features of relational databases and was tailored for efficient query answering. We consider a recently proposed temporal query language that combines conjunctive queries with the operators of propositional linear temporal logic (LTL). In particular, we consider negation in the ontology and query language, and study both data and combined complexity of query entailment.

scholarly journals Practical Querying of Temporal Data via OWL 2 QL and SQL:2011

10.29007/rlv9 ◽  
2018 ◽  
Author(s):  
Szymon Klarman
Keyword(s):  
Temporal Logic ◽  
Query Language ◽  
Practical Approach ◽  
Data Complexity ◽  
Temporal Data ◽  
First Order ◽  
Temporal Query ◽  
Temporal Query Language ◽  
Formal Properties ◽  
Semantic Layer

We develop a practical approach to querying temporal data stored in temporal SQL:2011 databases through the semantic layer of OWL 2 QL ontologies. An interval-based temporal query language (TQL), which we propose for this task, is defined via naturally characterizable combinations of temporal logic with conjunctive queries. This foundation warrants well-defined semantics and formal properties of TQL querying. In particular, we show that under certain mild restrictions the data complexity of query answering remains in AC$^0$, i.e., as in the usual, nontemporal case. On the practical side, TQL is tailored specifically to offer maximum expressivity while preserving the possibility of reusing standard first-order rewriting techniques and tools for OWL 2 QL.

Approaches to Semantics in Knowledge Management

2009 ◽  
pp. 257-281
Author(s):  
Cristiano Fugazza ◽  
Stefano David ◽  
Anna Montesanto ◽  
Cesare Rocchi
Keyword(s):  
Neural Networks ◽  
Knowledge Management ◽  
Artificial Neural Networks ◽  
Database Management ◽  
Description Logics ◽  
Open World ◽  
Open World Assumption ◽  
Relational Database Management ◽  
Static Nature ◽  
Relational Database Management Systems

There are different approaches to modeling a computational system, each providing different semantics. We present a comparison among different approaches to semantics and we aim at identifying which peculiarities are needed to provide a system with uniquely interpretable semantics. We discuss different approaches, namely, Description Logics, Artificial Neural Networks, and relational database management systems. We identify classification (the process of building a taxonomy) as common trait. However, in this chapter we also argue that classification is not enough to provide a system with a Semantics, which emerges only when relations among classes are established and used among instances. Our contribution also analyses additional features of the formalisms that distinguish the approaches: closed versus. open world assumption, dynamic versus. static nature of knowledge, the management of knowledge, and the learning process.

Design and implementation of a temporal query language with abstract time

1990 ◽  
Vol 15 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Jinho Kim ◽  
Hodong Yoo ◽  
Yoonjoon Lee
Keyword(s):  
Query Language ◽  
Design And Implementation ◽  
Temporal Query ◽  
Temporal Query Language

scholarly journals The temporal query language TQuel

1987 ◽  
Vol 12 (2) ◽  
pp. 247-298 ◽  
Author(s):  
Richard Snodgrass
Keyword(s):  
Query Language ◽  
Temporal Query ◽  
Temporal Query Language

scholarly journals Conjunctive Query Answering for the Description Logic SHIQ

2008 ◽  
Vol 31 ◽  
pp. 157-204 ◽  
Author(s):  
B. Glimm ◽  
C. Lutz ◽  
I. Horrocks ◽  
U. Sattler
Keyword(s):  
Description Logic ◽  
Query Language ◽  
Description Logics ◽  
Knowledge Bases ◽  
Deterministic Algorithm ◽  
Query Answering ◽  
Conjunctive Query ◽  
Conjunctive Queries ◽  
Complexity Bounds ◽  
Double Exponential

Conjunctive queries play an important role as an expressive query language for Description Logics (DLs). Although modern DLs usually provide for transitive roles, conjunctive query answering over DL knowledge bases is only poorly understood if transitive roles are admitted in the query. In this paper, we consider unions of conjunctive queries over knowledge bases formulated in the prominent DL SHIQ and allow transitive roles in both the query and the knowledge base. We show decidability of query answering in this setting and establish two tight complexity bounds: regarding combined complexity, we prove that there is a deterministic algorithm for query answering that needs time single exponential in the size of the KB and double exponential in the size of the query, which is optimal. Regarding data complexity, we prove containment in co-NP.

Announcement—the temporal query language TSQL2 final language definition

1994 ◽  
Vol 23 (3) ◽  
pp. 34 ◽  
Author(s):  
Richard Thomas Snodgrass ◽  
Ilsoo Ahn ◽  
Gad Ariav ◽  
Don Batory ◽  
James Clifford ◽  
...  
Keyword(s):  
Query Language ◽  
Temporal Query ◽  
Temporal Query Language ◽  
Language Definition

Reasoning with Vague Concepts in Description Logics

2017 ◽  
Vol 6 (2) ◽  
pp. 43-58
Author(s):  
Mohamed Gasmi ◽  
Mustapha Bourahla
Keyword(s):  
Description Logics ◽  
Formal Languages ◽  
The Third ◽  
Open World ◽  
Tableau Algorithm ◽  
Vague Concept ◽  
Open World Assumption

The open world assumption in ontologies representing knowledge may assign deficient (imprecise) meaning for ontology concepts which are language adjectives referring the meaning of classes of objects (individuals). The interpretation of an imprecise (vague) concept is by three subsets of individuals. The first subset of individuals surely belongs to the vague concept, the second subset of individuals surely doesn't belong the vague concept and the third subset is in the borderline. In this paper, the authors will show that is possible to describe ontology vague concepts using well-defined formal languages. The authors will propose also an extension of the Tableau algorithm for reasoning over vague ontologies.

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