Advanced Semantic Deep Search for 3D Scenes

Cao, Xiaoqi; Klusch, Matthias

doi:10.1109/icsc.2013.48

Cited by 2 publications

(2 citation statements)

References 21 publications

(24 reference statements)

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“…iRep3D [CK13, ZCK*13] enables semantic reflection of 3D models by analysing its syntactic, conceptual, functional and geometrical features. The method is used for 3D models encoded in X3D, XML3D and COLLADA.…”

Section: Classification Of Ontology‐based Approachesmentioning

confidence: 99%

Ontology‐Based Representation and Modelling of Synthetic 3D Content: A State‐of‐the‐Art Review

Flotyński

Walczak

2017

Computer Graphics Forum

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An indispensable element of any practical 3D/VR/AR application is synthetic three‐dimensional (3D) content. Such content is characterized by a variety of features—geometry, structure, space, appearance, animation and behaviour—which makes the modelling of 3D content a much more complex, difficult and time‐consuming task than in the case of other types of content. One of the promising research directions aiming at simplification of modelling 3D content is the use of the semantic web approach. The formalism provided by semantic web techniques enables declarative knowledge‐based modelling of content based on ontologies. Such modelling can be conducted at different levels of abstraction, possibly domain‐specific, with inherent separation of concerns. The use of semantic web ontologies enables content representation independent of particular presentation platforms and facilitates indexing, searching and analysing content, thus contributing to increased content re‐usability. A range of approaches have been proposed to permit semantic representation and modelling of synthetic 3D content. These approaches differ in the methodologies and technologies used as well as their scope and application domains. This paper provides a review of the current state of the art in representation and modelling of 3D content based on semantic web ontologies, together with a classification, characterization and discussion of the particular approaches.

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Section: Classification Of Ontology‐based Approachesmentioning

confidence: 99%

Ontology‐Based Representation and Modelling of Synthetic 3D Content: A State‐of‐the‐Art Review

Flotyński

Walczak

2017

Computer Graphics Forum

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“…The extraction of POI data from the network becomes an important means for obtaining data in the multiple areas such as application of urban planning. Researchers at home and abroad have carried out relevant research around the issues of network information acquisition and so on [2][3][4][5] . Liu Wei et al proposed a graph database-based web database sampling method.…”

Section: Introductionmentioning

confidence: 99%

Research on Deep Web POI Acquisition based on Retrieving Word Optimization and Spatial Adaption

Wang

Luo

Liu

et al. 2019

Proc. Int. Cartogr. Assoc.

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<p><strong>Abstract.</strong> POI data is a geographical information resource that is the most closely related to the public life, and has been successfully applied in various fields such as urban planning, urban logistics, and car navigation. With the development of technologies such as mobile networks and Internet of Things, the network contains a large number of high-value POI information resources. How to effectively acquire and utilize data resources has become a research hotspot in the field of spatial information. In this paper, a deep-web POI information search method based on independent coverage ranking and spatial adaptive partition is proposed to solve the problems of difficult construction of retrieval word base and limited data request. By constructing candidate search terms, searching greedily, optimizing dimensionality reduction of search terms, and crawling spatially adaptive partitioning, the maximum coverage optimal solution of POI search is approached step by step, and the full POI information of deep web is obtained. It is of great significance to improve the recall rate and collection efficiency of POI data for enriching geographic information resources and improving the ability of spatial information service and content management.</p>

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Advanced Semantic Deep Search for 3D Scenes

Cited by 2 publications

References 21 publications

Ontology‐Based Representation and Modelling of Synthetic 3D Content: A State‐of‐the‐Art Review

Ontology‐Based Representation and Modelling of Synthetic 3D Content: A State‐of‐the‐Art Review

Research on Deep Web POI Acquisition based on Retrieving Word Optimization and Spatial Adaption

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