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Knowledge graph construction with structure and parameter learning for indoor scene design

Liang, Yuan, Xu, Fei, Zhang, Song-Hai, Lai, Yukun ORCID: and Mu, Taijiang 2018. Knowledge graph construction with structure and parameter learning for indoor scene design. Computational Visual Media 4 (2) , pp. 123-137. 10.1007/s41095-018-0110-3

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We consider the problem of learning a representation of both spatial relations and dependencies between objects for indoor scene design. We propose a novel knowledge graph framework based on the entity-relation model for representation of facts in indoor scene design, and further develop a weaklysupervised algorithm for extracting the knowledge graph representation from a small dataset using both structure and parameter learning. The proposed framework is flexible, transferable, and readable. We present a variety of computer-aided indoor scene design applications using this representation, to show the usefulness and robustness of the proposed framework.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Springer
ISSN: 2096-0433
Date of First Compliant Deposit: 28 March 2018
Date of Acceptance: 13 January 2018
Last Modified: 11 May 2023 09:12

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