Minimalistic fuzzy ontology reasoning: An application to Building Information Modeling

Huitzil, Ignacio; Molina-Solana, Miguel; Gómez‐Romero, Juan; Bobillo, Fernando

doi:10.1016/j.asoc.2021.107158

Cited by 14 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In that directionality we were talking about, another developed work presents the naming of specific platforms based on the International Committee for Documentation Conceptual Reference Model (CIDOC CRM) [28], ontologies, but the connection is always the same through IFC files from HBIM. in ontology format, and the flow direction is unidirectional, that is, from the geometric model to the knowledge software [29]. Moves towards an experimental model a minimalistic reasoning algorithm to solve imprecise instance retrieval in fuzzy ontologies with application to querying Building Information Models.…”

Section: State Of Knowledgementioning

confidence: 99%

Semantic interoperability for cultural heritage conservation: Workflow from ontologies to a tool for managing and sharing data

Moyano,

Pili,

Nieto-Julián

et al. 2023

Journal of Building Engineering

View full text Add to dashboard Cite

Section: State Of Knowledgementioning

confidence: 99%

Semantic interoperability for cultural heritage conservation: Workflow from ontologies to a tool for managing and sharing data

Moyano,

Pili,

Nieto-Julián

et al. 2023

Journal of Building Engineering

View full text Add to dashboard Cite

“…The main advantage of this algorithm is that it is possible to reuse standard RDF language and SPARQL query endpoints, similarly as the authors in Huitzil et al (2020Huitzil et al ( , 2021 do for fuzzy ontologies.…”

Section: El 423mentioning

confidence: 99%

“…This makes it possible to reuse classical semantic reasoners (such as Sirin et al, 2007) and other existing resources. More recently, minimalist reasoning algorithms solve some flexible queries (restricted from an expressivity point of view) over classical ontologies by reusing classical semantic reasoners and building a fuzzy layer on top of them as a series of additional steps (Huitzil et al, 2020(Huitzil et al, , 2021.…”

Section: Introductionmentioning

confidence: 99%

FUKG: answering flexible queries over knowledge graphs

Yagüe,

Huitzil,

Bobed

et al. 2023

Self Cite

View full text Add to dashboard Cite

Purpose There is an increasing interest in the use of knowledge graphs to represent real-world knowledge and a common need to manage imprecise knowledge in many real-world applications. This paper aims to study approaches to solve flexible queries over knowledge graphs. Design/methodology/approach By introducing fuzzy logic in the query answering process, the authors are able to obtain a novel algorithm to solve flexible queries over knowledge graphs. This approach is implemented in the FUzzy Knowledge Graphs system, a software tool with an intuitive user-graphical interface. Findings This approach makes it possible to reuse semantic web standards (RDF, SPARQL and OWL 2) and builds a fuzzy layer on top of them. The application to a use case shows that the system can aggregate information in different ways by selecting different fusion operators and adapting to different user needs. Originality/value This approach is more general than similar previous works in the literature and provides a specific way to represent the flexible restrictions (using fuzzy OWL 2 datatypes).

show abstract

“…. " commands of a programming language), is considered as interchangeable data, susceptible to change [28]. It can be corrected, updated, and exploited by programs (inference engines), which simulate reasoning mechanisms and provide the interface with users [29].…”

Section: Intelligent Reasoning Of Irrhemmentioning

confidence: 99%

Intelligent Reasoning Rules for Home Energy Management (IRRHEM): Algeria Case Study

et al. 2022

View full text Add to dashboard Cite

Algeria is characterized by extreme cold in winter and high heat and humidity in summer. This leads to an increase in the use of electrical appliances, which has a negative impact on electrical energy consumption and its high costs, especially with the high price of electricity in Algeria. In this context, artificial intelligence can help to regulate the daily consumption of electricity, by optimizing the exploitation of natural resources and alerting the individual to avoid energy wasting. This paper proposes a decision-making tool (IRRHEM) for managing electrical energy at smart home. The IRRHEM solution is based on three elements: the use of natural resources, the notification of the inhabitants in case of resources misuse or wasting behavior, and the aggregation of similar activities at same time. Additionally, based on the proposed intelligent reasoning rules, residents’ behavior and activities are represented by OWL (Ontology Web Language) and written and executed through SWRL (Semantic Web Rule Language). Finally, the (IRRHEM) solution is tested in a home located in Algiers city inhabited by a family of four persons. The IRRHEM performance evaluation results are very promising and show a 3.60% rate of energy saving.

show abstract

Minimalistic fuzzy ontology reasoning: An application to Building Information Modeling

Cited by 14 publications

References 29 publications

Semantic interoperability for cultural heritage conservation: Workflow from ontologies to a tool for managing and sharing data

Semantic interoperability for cultural heritage conservation: Workflow from ontologies to a tool for managing and sharing data

FUKG: answering flexible queries over knowledge graphs

Intelligent Reasoning Rules for Home Energy Management (IRRHEM): Algeria Case Study

Contact Info

Product

Resources

About