Attributed Description Logics: Ontologies for Knowledge Graphs

Krötzsch, Markus; Marx, Maximilian; Ozaki, Ana; Thost, Veronika

doi:10.1007/978-3-319-68288-4_25

Cited by 11 publications

(18 citation statements)

References 16 publications

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“…We investigated the complexity of satisfiability and query answering in attributed DL-Lite R , for both the semantics introduced by Krötzsch et al (2017) and a new semantics based on provenance semirings, which allows to embed provenance polynomials into the query. In particular, we show that these problems are PSPACE-complete for the classical semantics and that in the case of simple ontologies, even query answering under the semirings-based semantics has the same complexity as query answering in DL-Lite R .…”

Section: Resultsmentioning

confidence: 99%

“…The first section introduces attributed DL-Lite R , following the formalism given by Krötzsch et al (2017;. We then define attributed conjunctive queries and study the complexity of satisfiability and query answering in attributed DL-Lite R .…”

Section: While the Work Bymentioning

confidence: 99%

“…A ground specifier is a closed or open specifier that only contains individual names. Intuitively, closed specifiers define specific annotation sets whereas open specifiers merely provide lower bounds (Krötzsch et al 2017).…”

Section: Attributed Dl-litementioning

confidence: 99%

“…In DL-Lite R @ , satisfiability is PSPACE-hard. To prove the PSPACE upper bound for satisfiability, we use grounding (Krötzsch et al 2017), which is a classical technique that consists in eliminating variables from an ontology to transform it into an equisatisfiable ground ontology. The ground ontology can then be translated into an equisatisfiable DL-Lite R ontology.…”

Section: Reasoning In Dl-lite R @mentioning

confidence: 99%

“…Property Graph, the data model used in many graph databases (Rodriguez and Neubauer 2010), and Wikidata, the knowledge graph used by Wikipedia (Vrandečić and Krötzsch 2014), are prominent examples of such labelled graphs. To bridge the gap between DL and knowledge graphs, attributed description logics (Krötzsch et al 2017;Krötzsch et al 2018) have been recently introduced. They enrich DL concepts and roles with finite sets of attribute-value pairs, called annotations, and allow to express constraints on these annotations in the ontology inclusions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Querying Attributed DL-Lite Ontologies Using Provenance Semirings

Bourgaux

Ozaki

2019

AAAI

Self Cite

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Attributed description logic is a recently proposed formalism, targeted for graph-based representation formats, which enriches description logic concepts and roles with finite sets of attribute-value pairs, called annotations. One of the most important uses of annotations is to record provenance information. In this work, we first investigate the complexity of satisfiability and query answering for attributed DL-LiteR ontologies. We then propose a new semantics, based on provenance semirings, for integrating provenance information with query answering. Finally, we establish complexity results for satisfiability and query answering under this semantics.

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Section: Resultsmentioning

confidence: 99%

Section: While the Work Bymentioning

confidence: 99%

Section: Attributed Dl-litementioning

confidence: 99%

Section: Reasoning In Dl-lite R @mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Querying Attributed DL-Lite Ontologies Using Provenance Semirings

Bourgaux

Ozaki

2019

AAAI

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Context-Aware Cognitive Agents using Knowledge Graphs for Automated Negotiation

Kröhling,

Chiotti,

Martínez

2024

2024 L Latin American Computer Conference (CLEI)

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Semantic Data Structures for Knowledge Generation in Open World Information System

Tibau

Siqueira

Nunes

2020

XVI Brazilian Symposium on Information Systems

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As the amount of information grows exponentially online, Information Systems role in support knowledge flows encouraged by linked data increases as a driver to innovation, culture, business practices and people behavior. Web search engines are particularly affected by the open world challenges, notably as part of the growing digital ecosystems of networks and platforms of technology, media, and telecommunications (TMT) companies delivering personalized and customized services (e.g. Amazon in retailing, Uber in ride service hailing, food delivery, and bicycle-sharing system, and Airbnb in lodging). To recognize search intent drawn from user's behavior allows to provide personalized search results. The work presented in this paper has the purpose of exploring methods to represent semantic relationships between concepts indexed by Web search engines in order to aid them recognize search intent and display results that meet the search intent. The performance of two different types of data structures based on entity-centric indexing was compared. The data structures were: a knowledge base that used an entity-centric mapping of Wikipedia categories and the KBpedia Knowledge Graph. Through analysis of entity ranking and linking, we detected that the Knowledge Graph could identify approximately three times more properties and relationships, which increases Web search engines capability to "understand" what is being asked.

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Attributed Description Logics: Ontologies for Knowledge Graphs

Cited by 11 publications

References 16 publications

Querying Attributed DL-Lite Ontologies Using Provenance Semirings

Querying Attributed DL-Lite Ontologies Using Provenance Semirings

Context-Aware Cognitive Agents using Knowledge Graphs for Automated Negotiation

Semantic Data Structures for Knowledge Generation in Open World Information System

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