Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature

10.1016/j.enbuild.2021.110885

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Bibliographic Details
Main Authors:	Abdelrahman, Mahmoud M, Zhan, Sicheng, Miller, Clayton, Chong, Adrian
Other Authors:	DEPT OF BUILDING
Format:	Article
Published:	Elsevier BV 2021
Subjects:	Reference mining natural language processing data science built environment building energy efficiency word embeddings
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/189541
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-189541
record_format	dspace
spelling	sg-nus-scholar.10635-1895412023-09-13T21:46:46Z Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature Abdelrahman, Mahmoud M Zhan, Sicheng Miller, Clayton Chong, Adrian DEPT OF BUILDING Reference mining natural language processing data science built environment building energy efficiency word embeddings 10.1016/j.enbuild.2021.110885 Energy and Buildings 110885-110885 completed 2021-04-16T08:17:09Z 2021-04-16T08:17:09Z 2021-03 2021-04-15T05:55:34Z Article Abdelrahman, Mahmoud M, Zhan, Sicheng, Miller, Clayton, Chong, Adrian (2021-03). Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature. Energy and Buildings : 110885-110885. ScholarBank@NUS Repository. https://doi.org/10.1016/j.enbuild.2021.110885 03787788 https://scholarbank.nus.edu.sg/handle/10635/189541 Elsevier BV Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Reference mining natural language processing data science built environment building energy efficiency word embeddings
spellingShingle	Reference mining natural language processing data science built environment building energy efficiency word embeddings Abdelrahman, Mahmoud M Zhan, Sicheng Miller, Clayton Chong, Adrian Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
description	10.1016/j.enbuild.2021.110885
author2	DEPT OF BUILDING
author_facet	DEPT OF BUILDING Abdelrahman, Mahmoud M Zhan, Sicheng Miller, Clayton Chong, Adrian
format	Article
author	Abdelrahman, Mahmoud M Zhan, Sicheng Miller, Clayton Chong, Adrian
author_sort	Abdelrahman, Mahmoud M
title	Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
title_short	Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
title_full	Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
title_fullStr	Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
title_full_unstemmed	Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature
title_sort	data science for building energy efficiency: a comprehensive text-mining driven review of scientific literature
publisher	Elsevier BV
publishDate	2021
url	https://scholarbank.nus.edu.sg/handle/10635/189541
_version_	1779153347717103616

Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature

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