Leveraging Word Embeddings and Transformers to Extract Semantics from Building Regulations Text

Odinakachukwu Okonkwo; Amna Dridi; Edlira Vakaj

Leveraging Word Embeddings and Transformers to Extract Semantics from Building Regulations Text

Odinakachukwu Okonkwo, Amna Dridi^*, Edlira Vakaj

^*Corresponding author for this work

Birmingham City University

Research output: Contribution to journal › Conference article › peer-review

1 Citation (SciVal)

Original language	English
Pages (from-to)	176-188
Number of pages	13
Journal	CEUR Workshop Proceedings
Volume	3633
Publication status	Published (VoR) - 2023
Event	11th Linked Data in Architecture and Construction Workshop, LDAC 2023 - Matera, Italy Duration: 15 Jul 2023 → 16 Jul 2023

Funding

This work is partially funded by the European Union’s Horizon Europe research and innovation programme under grant agreement no 101056973 (ACCORD). UK Participants in Horizon Europe Project [ACCORD] are supported by UKRI grant numbers [10040207] (Cardiff University), [10038999 ] (Birmingham City University and [10049977] (Building Smart International).

Funders	Funder number
ACCORD
European Union’s Horizon Europe research and innovation programme	101056973
Horizon Europe Project
Birmingham City University	10049977
UK Research and Innovation	10040207
Cardiff University	10038999

Keywords

AEC domain
BERT
Building regulations
Machine Learning
Natural Language Processing
Semantic regulations
Sentence BERT
Transformers
Word embeddings
word2vec

Cite this

@article{850aee646dd448788ca511c40febbe2a,

title = "Leveraging Word Embeddings and Transformers to Extract Semantics from Building Regulations Text",

keywords = "AEC domain, BERT, Building regulations, Machine Learning, Natural Language Processing, Semantic regulations, Sentence BERT, Transformers, Word embeddings, word2vec",

author = "Odinakachukwu Okonkwo and Amna Dridi and Edlira Vakaj",

note = "Publisher Copyright: {\textcopyright} 2023 Copyright for this paper by its authors.; 11th Linked Data in Architecture and Construction Workshop, LDAC 2023 ; Conference date: 15-07-2023 Through 16-07-2023",

year = "2023",

language = "English",

volume = "3633",

pages = "176--188",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

}

TY - JOUR

T1 - Leveraging Word Embeddings and Transformers to Extract Semantics from Building Regulations Text

AU - Okonkwo, Odinakachukwu

AU - Dridi, Amna

AU - Vakaj, Edlira

PY - 2023

Y1 - 2023

KW - AEC domain

KW - BERT

KW - Building regulations

KW - Machine Learning

KW - Natural Language Processing

KW - Semantic regulations

KW - Sentence BERT

KW - Transformers

KW - Word embeddings

KW - word2vec

UR - https://www.scopus.com/pages/publications/85184383989

UR - https://www.scopus.com/inward/citedby.url?scp=85184383989&partnerID=8YFLogxK

UR - https://www.open-access.bcu.ac.uk/15260/

M3 - Conference article

AN - SCOPUS:85184383989

SN - 1613-0073

VL - 3633

SP - 176

EP - 188

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 11th Linked Data in Architecture and Construction Workshop, LDAC 2023

Y2 - 15 July 2023 through 16 July 2023

ER -

Leveraging Word Embeddings and Transformers to Extract Semantics from Building Regulations Text

Funding

Keywords

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Cite this