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Almeida, L, Tam, V W, Le, K N and She, Y (2020) Effects of occupant behaviour on energy performance in buildings: a green and non-green building comparison. Engineering, Construction and Architectural Management, 27(08), 1939–62.

Hu, W, Dong, J, Hwang, B, Ren, R and Chen, Z (2020) Network planning of urban underground logistics system with hub-and-spoke layout: two phase cluster-based approach. Engineering, Construction and Architectural Management, 27(08), 2079–105.

Jeelani, I, Han, K and Albert, A (2020) Development of virtual reality and stereo-panoramic environments for construction safety training. Engineering, Construction and Architectural Management, 27(08), 1853–76.

Ji, Y, Qi, K, Qi, Y, Li, Y, Li, H X, Lei, Z and Liu, Y (2020) BIM-based life-cycle environmental assessment of prefabricated buildings. Engineering, Construction and Architectural Management, 27(08), 1703–25.

Li, H X, Ma, Z, Liu, H, Wang, J, Al-Hussein, M and Mills, A (2020) Exploring and verifying BIM-based energy simulation for building operations. Engineering, Construction and Architectural Management, 27(08), 1679–702.

Li, Q, Sun, Q, Tao, S and Gao, X (2019) Multi-skill project scheduling with skill evolution and cooperation effectiveness. Engineering, Construction and Architectural Management, 27(08), 2023–45.

Li, X, Li, J, Zhang, X, Gao, J and Zhang, C (2020) Simplified analysis of cable-stayed bridges with longitudinal viscous dampers. Engineering, Construction and Architectural Management, 27(08), 1993–2022.

Lu, H, Qi, J, Li, J, Xie, Y, Xu, G and Wang, H (2020) Multi-agent based safety computational experiment system for shield tunneling projects. Engineering, Construction and Architectural Management, 27(08), 1963–91.

Meng, Q, Zhang, Y, Li, Z, Shi, W, Wang, J, Sun, Y, Xu, L and Wang, X (2020) A review of integrated applications of BIM and related technologies in whole building life cycle. Engineering, Construction and Architectural Management, 27(08), 1647–77.

Stride, M, Hon, C K, Liu, R and Xia, B (2020) The use of building information modelling by quantity surveyors in facilities management roles. Engineering, Construction and Architectural Management, 27(08), 1795–812.

Tang, L, Griffith, L, Stevens, M and Hardie, M (2020) Social media analytics in the construction industry comparison study between China and the United States. Engineering, Construction and Architectural Management, 27(08), 1877–89.

Wu, H, Shen, G, Lin, X, Li, M, Zhang, B and Li, C Z (2020) Screening patents of ICT in construction using deep learning and NLP techniques. Engineering, Construction and Architectural Management, 27(08), 1891–912.

  • Type: Journal Article
  • Keywords: ICT in construction; NLP; Deep learning; Information management;
  • ISBN/ISSN: 0969-9988
  • URL: https://doi.org/10.1108/ECAM-09-2019-0480
  • Abstract:
    This study proposes an approach to solve the fundamental problem in using query-based methods (i.e. searching engines and patent retrieval tools) to screen patents of information and communication technology in construction (ICTC). The fundamental problem is that ICTC incorporates various techniques and thus cannot be simply represented by man-made queries. To investigate this concern, this study develops a binary classifier by utilizing deep learning and NLP techniques to automatically identify whether a patent is relevant to ICTC, thus accurately screening a corpus of ICTC patents.Design/methodology/approach This study employs NLP techniques to convert the textual data of patents into numerical vectors. Then, a supervised deep learning model is developed to learn the relations between the input vectors and outputs.Findings The validation results indicate that (1) the proposed approach has a better performance in screening ICTC patents than traditional machine learning methods; (2) besides the United States Patent and Trademark Office (USPTO) that provides structured and well-written patents, the approach could also accurately screen patents form Derwent Innovations Index (DIX), in which patents are written in different genres.Practical implications This study contributes a specific collection for ICTC patents, which is not provided by the patent offices.Social implications The proposed approach contributes an alternative manner in gathering a corpus of patents for domains like ICTC that neither exists as a searchable classification in patent offices, nor is accurately represented by man-made queries.Originality/value A deep learning model with two layers of neurons is developed to learn the non-linear relations between the input features and outputs providing better performance than traditional machine learning models. This study uses advanced NLP techniques lemmatization and part-of-speech POS to process textual data of ICTC patents. This study contributes specific collection for ICTC patents which is not provided by the patent offices.

Xie, X, Lu, Q, Rodenas-Herraiz, D, Parlikad, A K and Schooling, J M (2020) Visualised inspection system for monitoring environmental anomalies during daily operation and maintenance. Engineering, Construction and Architectural Management, 27(08), 1835–52.

Xu, M, Mei, Z, Luo, S and Tan, Y (2020) Optimization algorithms for construction site layout planning: a systematic literature review. Engineering, Construction and Architectural Management, 27(08), 1913–38.

Xu, W and Wang, T (2020) Dynamic safety prewarning mechanism of human–machine–environment using computer vision. Engineering, Construction and Architectural Management, 27(08), 1813–33.

Xu, Z, Wang, X, Xiao, Y and Yuan, J (2020) Modeling and performance evaluation of PPP projects utilizing IFC extension and enhanced matter-element method. Engineering, Construction and Architectural Management, 27(08), 1763–94.

Yuan, J, Li, X, Ke, Y, Xu, W and Xu, Z (2020) Developing a building information modeling–based performance management system for public–private partnerships. Engineering, Construction and Architectural Management, 27(08), 1727–62.

Zhang, J, Ouyang, Y, Li, H, Ballesteros-Pérez, P and Skitmore, M (2020) Simulation analysis of incentives on employees' acceptance of foreign joint venture management practices: a case study. Engineering, Construction and Architectural Management, 27(08), 2047–78.