Approach to capturing design requirements from the existing architectural documents using natural language processing technique

Jae Yeol Song, Jin Sung Kim, Hayan Kim, Jungsik Choi, Jin Kook Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes an approach to utilizing natural language processing (NLP) to capture design requirements from the natural language-based architectural documents. In various design stage of the architectural process, there are several different kinds of documents describing requirements for buildings. Capturing the design requirements from those documents is based on extracting information of objects, their properties, and relations. Until recently, interpreting and extracting that information from documents are almost done by a manual process. To intelligently automate the conventional process, the computer has to understand the semantics of natural languages. In this regards, this paper suggests an approach to utilizing NLP for semantic analysis which enables the computer to understand the semantics of the given text data. The proposed approach has following steps: 1) extract noun words which mostly represent objects and property data in Korean Building Act; 2) analyze the semantic relations between words, using NLP and deep learning; 3) Based on domain database, translate the noun words in objects and properties data and find out their relations.

Original languageEnglish
Title of host publicationCAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia
Subtitle of host publicationLearning, Prototyping and Adapting
EditorsSuleiman Alhadidi, Tomohiro Fukuda, Weixin Huang, Patrick Janssen, Kristof Crolla
PublisherThe Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)
Pages247-254
Number of pages8
ISBN (Electronic)9789887891703
Publication statusPublished - 2018 Jan 1
Event23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting, CAADRIA 2018 - Beijing, China
Duration: 2018 May 172018 May 19

Publication series

NameCAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting
Volume2

Other

Other23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting, CAADRIA 2018
CountryChina
CityBeijing
Period18/5/1718/5/19

Fingerprint

Semantics
Processing

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Building and Construction

Cite this

Song, J. Y., Kim, J. S., Kim, H., Choi, J., & Lee, J. K. (2018). Approach to capturing design requirements from the existing architectural documents using natural language processing technique. In S. Alhadidi, T. Fukuda, W. Huang, P. Janssen, & K. Crolla (Eds.), CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting (pp. 247-254). (CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting; Vol. 2). The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA).
Song, Jae Yeol ; Kim, Jin Sung ; Kim, Hayan ; Choi, Jungsik ; Lee, Jin Kook. / Approach to capturing design requirements from the existing architectural documents using natural language processing technique. CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting. editor / Suleiman Alhadidi ; Tomohiro Fukuda ; Weixin Huang ; Patrick Janssen ; Kristof Crolla. The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 2018. pp. 247-254 (CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting).
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Song, JY, Kim, JS, Kim, H, Choi, J & Lee, JK 2018, Approach to capturing design requirements from the existing architectural documents using natural language processing technique. in S Alhadidi, T Fukuda, W Huang, P Janssen & K Crolla (eds), CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting. CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting, vol. 2, The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), pp. 247-254, 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting, CAADRIA 2018, Beijing, China, 18/5/17.

Approach to capturing design requirements from the existing architectural documents using natural language processing technique. / Song, Jae Yeol; Kim, Jin Sung; Kim, Hayan; Choi, Jungsik; Lee, Jin Kook.

CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting. ed. / Suleiman Alhadidi; Tomohiro Fukuda; Weixin Huang; Patrick Janssen; Kristof Crolla. The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), 2018. p. 247-254 (CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting; Vol. 2).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This paper describes an approach to utilizing natural language processing (NLP) to capture design requirements from the natural language-based architectural documents. In various design stage of the architectural process, there are several different kinds of documents describing requirements for buildings. Capturing the design requirements from those documents is based on extracting information of objects, their properties, and relations. Until recently, interpreting and extracting that information from documents are almost done by a manual process. To intelligently automate the conventional process, the computer has to understand the semantics of natural languages. In this regards, this paper suggests an approach to utilizing NLP for semantic analysis which enables the computer to understand the semantics of the given text data. The proposed approach has following steps: 1) extract noun words which mostly represent objects and property data in Korean Building Act; 2) analyze the semantic relations between words, using NLP and deep learning; 3) Based on domain database, translate the noun words in objects and properties data and find out their relations.

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ER -

Song JY, Kim JS, Kim H, Choi J, Lee JK. Approach to capturing design requirements from the existing architectural documents using natural language processing technique. In Alhadidi S, Fukuda T, Huang W, Janssen P, Crolla K, editors, CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting. The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA). 2018. p. 247-254. (CAADRIA 2018 - 23rd International Conference on Computer-Aided Architectural Design Research in Asia: Learning, Prototyping and Adapting).