Backward Reasoning in Aboxes for Query Answering.

The plan goal is given in terms of satisfaction of a DL query. ... In this paper we address the problem of planning in rich domains, where knowledge representation is a key aspect for managing the complexity and size of the planning domain. ... The research presented in this paper has been partially funded by the EU project ASCENS (nr.257414) and by the Italian MIUR PRIN project CINA (2010LHT4KM). ...

doi:10.4204/eptcs.159.8 fatcat:ojwsbc4hunhxtj7uf7nvnbc2fu

DOAJ Multiple Versions

According to these approaches, queries formulated in an ontology describing the knowledge domain as a whole are translated into queries formulated in vocabularies of integrated data sources. ... In this paper we provide an alternative approach for efficient federated debugging. ... This research has been partially supported by the SE-MANCO project (http://www.semanco-project.eu), which is being carried out with the support of the Seventh Framework Programme "ICT for Energy Systems ...

doi:10.1007/978-3-319-11113-1_17 fatcat:g2bnxbi7bnhazev6dmcxqhzfta

Recently, many methods have been developed for representing knowledge, reasoning, and result extraction extracting results based on the respective domain knowledge in question. ... The main challenge in ontology reasoning methods is the failure in solving realization problems in the reasoning process. ... The authors of [38] present the a reasoner based on conjunctive query answering for DL programs. ...

doi:10.22452/mjcs.vol35no1.3 fatcat:lmsottx43vh5xnkph3ra2mzdmu

Our approach combines a reduction with a decomposed backwards chaining algorithm for OMQs that are based on the simpler atomic queries, also illuminating the relationship between first-order rewritings ... We consider the case where the ontology is formulated in the description logic EL and the actual query is a conjunctive query and show that rewritings of such OMQs can be efficiently computed in practice ... This follows from (a minor variation of) an observation from [4] : FO-rewritability of non-Boolean OMQs from (EL, CQ) can be reduced to a combination of containment in (EL, CQ) and FO-rewritability in ...

doi:10.1007/978-3-319-68288-4_21 fatcat:nrynnalwdbdthnbjbf5i74c4pi

Multiple Versions

For multimedia interpretation, and in particular for the combined interpretation of information coming from different modalities, a semantically well-founded formalization is required in the context of ... We propose an abduction-based formalism that uses description logics for the ontology and Horn rules for defining the space of hypotheses for explanations (i.e., the space of possible interpretations of ... answer a query. ...

doi:10.1007/978-3-642-15918-3_15 fatcat:bplgcif54vaurprbdhv54uphea

As such, SPARQL query answering on OWL ontologies could be solved in databases. ... We believe such a processing suitable to capture ontologies in the database flavor, while keeping reasoning tractable. ... data, with query answering as an underlying reasoning service. ...

doi:10.1007/11926078_32 fatcat:fq7fotzxlja2hmfiix3hhbr36u

The partitions are designed such that each can be reasoned on independently to find answers to each query subgoal, and when the results are unioned together, a complete set of results are found for that ... All slaves run in parallel, each performing sound and complete reasoning to execute each subgoal of its query on its own set of partitions. ... They introduce optimizations to reduce the search space of backward-chaining reasoning. However, they show query evaluation for only single pattern queries, not conjunctive queries. ...

doi:10.1109/icsc.2014.34 dblp:conf/semco/PriyaGSH14 fatcat:rla7xisblzcm5jfhxc4henlnti

DLs and Data Access 3.1 Conjunctive Query Answering in DLs 3.2 Query Answering in Lightweight DLs 3.3 Query Answering in Expressive DLs 3.4 Summary 2. ... DLs and Data Access 3.1 Conjunctive Query Answering in DLs 3.2 Query Answering in Lightweight DLs 3.3 Query Answering in Expressive DLs 3.4 Summary 2. ... be matched to a tree in exponentially many different ways Deciding I |= Q inside a tree is exponentially harder than standard reasoning Many algorithms for query answering in expressive DLs have been ...

doi:10.1007/978-3-642-33158-9_1 fatcat:fzifcfpzwndgrng6jfjeldipxe

In this tutorial, we give an overview of state-of-the art query languages and engines for temporal and stream reasoning. ... On a more detailed level, we discuss the new language STARQL (Reasoning-based Query Language for Streaming and Temporal ontology Access). ... reasoning services such as subsumption testing, satisfiability testing, query answering etc. ...

doi:10.1007/978-3-319-10587-1_7 fatcat:hxxseki2izf7ndwrrnpfzwvofe

Besides standard query answering, there is also a need for such systems to be coupled with explanation facilities, in particular to explain missing query answers (i.e. desired answers of a query which ... In this paper, we present a hybrid approach to achieve this. ... First, while ontology-based reasoning empowers query answering, it also complicates query abduction. The computational complexity of query abduction is indeed higher than query answering [6] . ...

doi:10.1145/2806416.2806547 dblp:conf/cikm/WangCWD15 fatcat:klcjrmqe5ndltgrdo32je7stea

This class guarantees that instance retrieval for an atomic negation can be reduced to answering a disjunction of conjunctive queries (CQs) over the ABox. ... Although it is a popular task for ontology reasoning, there is no scalable method for instance retrieval for negated concepts by now. ... Rewriting-based Instance Retrieval Query rewriting is an efficient and scalable approach to reasoning over ontologies that are expressed in lightweight DLs and have large ABoxes. ...

doi:10.1007/978-3-319-25007-6_20 fatcat:ujxrwruzyjgphna7ebxxwc7yam

In order to build video training sets and to enrich the proposed ontology, manual video annotation is performed based on background knowledge formalized in an ontology, representing a semantics of a traditional ... Second, we address the question of how can end-users efficiently query the datasets of annotated videos that are built. ... Querying ABoxes In this section, we propose an OMQA approach for querying KBs representing Zapin dances. We take the reasonable assumption stating that the TBox is stable, coherent and reliable. ...

doi:10.1109/ictai.2019.00239 dblp:conf/ictai/BelabbesTVITLB19 fatcat:w3mkoky56zc75boqi2iisejvtm

The second issue tackled in this work is explaining why a tuple is a (non-)answer to a query under these semantics. ... The first contribution of this paper is a practical approach for computing the query answers under three well-known such semantics, namely the AR, IAR and brave semantics, in the lightweight description ... For this reason, we choose to focus on ABox assertions, rather than TBox axioms. ...

doi:10.1613/jair.1.11395 fatcat:5o7b52euq5duhei6m4mrp2lnba

DOAJ Szczepanski

for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. ... In this sense, they are the first Description Logics specifically tailored for effective query answering over very large ABoxes. * This paper is an extended and abridged version of [10] ... We observe that query answering (properly) generalizes a well known reasoning service in DLs, namely instance checking, i.e., logical implication of an ABox assertion. ...

doi:10.1016/j.artint.2012.10.003 fatcat:yulvaclpwzhwhp7cv3mwbc7enu

Szczepanski

We propose a framework for querying probabilistic instance data in the presence of an OWL2 QL ontology, arguing that the interplay of probabilities and ontologies is fruitful in many applications such ... We also demonstrate that query rewriting (backwards chaining) is an important tool for our framework, show that non-existence of a rewriting into first-order logic implies #P-hardness, and briefly discuss ... As a central tool, we use query rewriting (also called backwards chaining), which is an important technique for traditional ontology based data access (OBDA), i.e., answering CQs in the presence of a DL-Lite ...

doi:10.1007/978-3-642-35176-1_12 fatcat:zgkgwxaoprbebmey3hzwa3k4sq

Backwards State-space Reduction for Planning in Dynamic Knowledge Bases

Preserved Fulltext

Efficient Federated Debugging of Lightweight Ontologies [chapter]

Preserved Fulltext

A METHOD FOR IMPROVING REASONING AND REALIZATION PROBLEM SOLVING IN DESCRIPTIVE LOGIC- BASED AND ONTOLOGY-BASED REASONERS

Preserved Fulltext

Computing FO-Rewritings in $$\mathcal{EL}$$ in Practice: From Atomic to Conjunctive Queries [chapter]

Preserved Fulltext

Other Versions

A Probabilistic Abduction Engine for Media Interpretation Based on Ontologies [chapter]

Preserved Fulltext

Ontology Query Answering on Databases [chapter]

Preserved Fulltext

Partitioning OWL Knowledge Bases for Parallel Reasoning

Preserved Fulltext

Reasoning and Query Answering in Description Logics [chapter]

Preserved Fulltext

Ontology Based Data Access on Temporal and Streaming Data [chapter]

Preserved Fulltext

Towards Scalable and Complete Query Explanation with OWL 2 EL Ontologies

Preserved Fulltext

Rewriting-Based Instance Retrieval for Negated Concepts in Description Logic Ontologies [chapter]

Preserved Fulltext

Query Answering from Traditional Dance Videos: Case Study of Zapin Dances

Preserved Fulltext

Computing and Explaining Query Answers over Inconsistent DL-Lite Knowledge Bases

Preserved Fulltext

Data complexity of query answering in description logics

Preserved Fulltext

Ontology-Based Access to Probabilistic Data with OWL QL [chapter]

Preserved Fulltext