IfcWoD, Semantically Adapting IFC Model Relations into OWL Properties
In the context of Building Information Modelling, ontologies have been identified as interesting in achieving information interoperability. Regarding the construction and facility management domains, several IFC (Industry Foundation Classes) based ontologies have been developed, such as IfcOWL. In the context of ontology modelling, the constraint of optimizing the size of IFC STEP-based files can be leveraged. In this paper, we propose an adaptation of the IFC model into OWL which leverages from all modelling constraints required by the object-oriented structure of IFC schema. Therefore, we do not only present a syntactic but also a semantic adaptation of the IFC model. Our model takes into consideration the meaning of entities, relationships, properties and attributes defined by the IFC standard. Our approach presents several advantages compared to other initiatives such as the optimization of query execution time. Every advantage is defended by means of practical examples and benchmarks.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementSimilar Papers 제목 키워드 기반
Semantic Enrichment of the Quantum Cascade Laser Properties in Text- A Knowledge Graph Generation Approach
A well structured collection of the various Quantum Cascade Laser (QCL) design and working properties data provides a platform to analyze and understand the relationships between these properties. By analyzing these rela…
Graph GenerationKnowledge GraphsRAGRetrieval-augmented GenerationInvestigating Antigram Behaviour using Distributional Semantics
The field of computational linguistics constantly presents new challenges and topics for research. Whether it be analyzing word usage changes over time or identifying relationships between pairs of seemingly unrelated wo…
Semantic SimilaritySemantic Textual SimilarityDINO Eats CLIP: Adapting Beyond Knowns for Open-set 3D Object Retrieval
Vision foundation models have shown great promise for open-set 3D object retrieval (3DOR) through efficient adaptation to multi-view images. Leveraging semantically aligned latent space, previous work typically adapts th…
3D Object RetrievalCLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs
We present CLAMP-ViT, a data-free post-training quantization method for vision transformers (ViTs). We identify the limitations of recent techniques, notably their inability to leverage meaningful inter-patch relationshi…
Contrastive Learningobject-detectionObject DetectionQuantizationG2L: Semantically Aligned and Uniform Video Grounding via Geodesic and Game Theory
The recent video grounding works attempt to introduce vanilla contrastive learning into video grounding. However, we claim that this naive solution is suboptimal. Contrastive learning requires two key properties: (1) \em…
Contrastive LearningVideo Grounding