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Article: A Domain Knowledge Incorporated Text-Mining Approach for Capturing User Needs on BIM Applications

TitleA Domain Knowledge Incorporated Text-Mining Approach for Capturing User Needs on BIM Applications
Authors
KeywordsBuilding information modelling
Information and communication technology (ICT) applications
Technology
Text mining
User needs
Issue Date2019
PublisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/ecam.htm
Citation
Engineering, Construction and Architectural Management, 2019, Epub How to Cite?
AbstractPurpose: In the architecture, engineering and construction (AEC) industry, technology developers have difficulties in fully understanding user needs due to the high domain knowledge threshold and the lack of effective and efficient methods to minimise information asymmetry between technology developers and AEC users. The paper aims to discuss this issue. Design/methodology/approach: A synthetic approach combining domain knowledge and text mining techniques is proposed to help capture user needs, which is demonstrated using building information modelling (BIM) apps as a case. The synthetic approach includes the: collection and cleansing of BIM apps’ attribute data and users’ comments; incorporation of domain knowledge into the collected comments; performance of a sentiment analysis to distinguish positive and negative comments; exploration of the relationships between user sentiments and BIM apps’ attributes to unveil user preferences; and establishment of a topic model to identify problems frequently raised by users. Findings: The results show that those BIM app categories with high user interest but low sentiments or supplies, such as “reality capture”, “interoperability” and “structural simulation and analysis”, should deserve greater efforts and attention from developers. BIM apps with continual updates and of small size are more preferred by users. Problems related to the “support for new Revit”, “import & export” and “external linkage” are most frequently complained by users. Originality/value: The main contributions of this work include: the innovative application of text mining techniques to identify user needs to drive BIM apps development; and the development of a synthetic approach to orchestrating domain knowledge, text mining techniques (i.e. sentiment analysis and topic modelling) and statistical methods in order to help extract user needs for promoting the success of emerging technologies in the AEC industry. © 2019, Emerald Publishing Limited.
Persistent Identifierhttp://hdl.handle.net/10722/273852
ISSN
2017 Impact Factor: 1.613
2015 SCImago Journal Rankings: 0.541

 

DC FieldValueLanguage
dc.contributor.authorZhou, S-
dc.contributor.authorNg, ST-
dc.contributor.authorLee, SH-
dc.contributor.authorXu, J-
dc.contributor.authorYang, Y-
dc.date.accessioned2019-08-18T14:49:53Z-
dc.date.available2019-08-18T14:49:53Z-
dc.date.issued2019-
dc.identifier.citationEngineering, Construction and Architectural Management, 2019, Epub-
dc.identifier.issn0969-9988-
dc.identifier.urihttp://hdl.handle.net/10722/273852-
dc.description.abstractPurpose: In the architecture, engineering and construction (AEC) industry, technology developers have difficulties in fully understanding user needs due to the high domain knowledge threshold and the lack of effective and efficient methods to minimise information asymmetry between technology developers and AEC users. The paper aims to discuss this issue. Design/methodology/approach: A synthetic approach combining domain knowledge and text mining techniques is proposed to help capture user needs, which is demonstrated using building information modelling (BIM) apps as a case. The synthetic approach includes the: collection and cleansing of BIM apps’ attribute data and users’ comments; incorporation of domain knowledge into the collected comments; performance of a sentiment analysis to distinguish positive and negative comments; exploration of the relationships between user sentiments and BIM apps’ attributes to unveil user preferences; and establishment of a topic model to identify problems frequently raised by users. Findings: The results show that those BIM app categories with high user interest but low sentiments or supplies, such as “reality capture”, “interoperability” and “structural simulation and analysis”, should deserve greater efforts and attention from developers. BIM apps with continual updates and of small size are more preferred by users. Problems related to the “support for new Revit”, “import & export” and “external linkage” are most frequently complained by users. Originality/value: The main contributions of this work include: the innovative application of text mining techniques to identify user needs to drive BIM apps development; and the development of a synthetic approach to orchestrating domain knowledge, text mining techniques (i.e. sentiment analysis and topic modelling) and statistical methods in order to help extract user needs for promoting the success of emerging technologies in the AEC industry. © 2019, Emerald Publishing Limited.-
dc.languageeng-
dc.publisherEmerald Group Publishing Limited. The Journal's web site is located at http://www.emeraldinsight.com/ecam.htm-
dc.relation.ispartofEngineering, Construction and Architectural Management-
dc.subjectBuilding information modelling-
dc.subjectInformation and communication technology (ICT) applications-
dc.subjectTechnology-
dc.subjectText mining-
dc.subjectUser needs-
dc.titleA Domain Knowledge Incorporated Text-Mining Approach for Capturing User Needs on BIM Applications-
dc.typeArticle-
dc.identifier.emailNg, ST: tstng@hku.hk-
dc.identifier.emailLee, SH: shlee1@hku.hk-
dc.identifier.emailXu, J: frankxu@hkucc.hku.hk-
dc.identifier.authorityNg, ST=rp00158-
dc.identifier.authorityLee, SH=rp01910-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1108/ECAM-02-2019-0097-
dc.identifier.scopuseid_2-s2.0-85071948472-
dc.identifier.hkuros301886-
dc.publisher.placeUnited Kingdom-

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