ARCOM

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Adekunle, T O (2019) Field measurements of comfort, seasonal performance and cold stress in cross-laminated timber (CLT) school buildings. Smart and Sustainable Built Environment, 9(04), 655–73.

Aggarwal, A, Rani, A and Kumar, M (2019) A robust method to authenticate car license plates using segmentation and ROI based approach. Smart and Sustainable Built Environment, 9(04), 737–47.

Aggarwal, T and Solomon, P (2019) Quantitative analysis of the development of smart cities in India. Smart and Sustainable Built Environment, 9(04), 711–26.

Agyekum, K, Adinyira, E and Ampratwum, G (2020) Factors driving the adoption of green certification of buildings in Ghana. Smart and Sustainable Built Environment, 9(04), 595–613.

Dell'Anna, F, Bottero, M, Becchio, C, Corgnati, S P and Mondini, G (2020) Designing a decision support system to evaluate the environmental and extra-economic performances of a nearly zero-energy building. Smart and Sustainable Built Environment, 9(04), 413–42.

Dewan, S and Singh, L (2020) Use of blockchain in designing smart city. Smart and Sustainable Built Environment, 9(04), 695–709.

du Toit, J and Wagner, C (2020) The effect of housing type on householders' self-reported participation in recycling. Smart and Sustainable Built Environment, 9(04), 395–412.

Ekemode, B G (2019) Impact of urban regeneration on commercial property values in Osogbo, Osun State, Nigeria. Smart and Sustainable Built Environment, 9(04), 557–71.

Eslamirad, N, Malekpour Kolbadinejad, S, Mahdavinejad, M and Mehranrad, M (2020) Thermal comfort prediction by applying supervised machine learning in green sidewalks of Tehran. Smart and Sustainable Built Environment, 9(04), 361–74.

Hussein, D (2020) A user preference modelling method for the assessment of visual complexity in building façade. Smart and Sustainable Built Environment, 9(04), 483–501.

Khan, N A, Ullah Khan, S, Ahmed, S, Farooqi, I H, Hussain, A, Vambol, S and Vambol, V (2019) Smart ways of hospital wastewater management, regulatory standards and conventional treatment techniques. Smart and Sustainable Built Environment, 9(04), 727–36.

Konstantinou, T, de Jonge, T, Oorschot, L, El Messlaki, S, van Oel, C and Asselbergs, T (2019) The relation of energy efficiency upgrades and cost of living, investigated in two cases of multi-residential buildings in the Netherlands. Smart and Sustainable Built Environment, 9(04), 615–33.

Kumar, A, Jain, S and Yadav, D (2020) A novel simulation-annealing enabled ranking and scaling statistical simulation constrained optimization algorithm for Internet-of-things (IoTs). Smart and Sustainable Built Environment, 9(04), 675–93.

Lau, J L and Hashim, A H (2019) Mediation analysis of the relationship between environmental concern and intention to adopt green concepts. Smart and Sustainable Built Environment, 9(04), 539–56.

Moshtaghian, F, Golabchi, M and Noorzai, E (2020) A framework to dynamic identification of project risks. Smart and Sustainable Built Environment, 9(04), 375–93.

Ndlangamandla, M G and Combrinck, C (2019) Environmental sustainability of construction practices in informal settlements. Smart and Sustainable Built Environment, 9(04), 523–38.

Opawole, A, Babatunde, S O, Kajimo-Shakantu, K and Ateji, O A (2020) Analysis of barriers to the application of life cycle costing in building projects in developing countries. Smart and Sustainable Built Environment, 9(04), 503–21.

Saadi, A and Belhadef, H (2020) Deep neural networks for Arabic information extraction. Smart and Sustainable Built Environment, 9(04), 467–82.

• Type: Journal Article
• Keywords: Deep neural networks; Part-of-speech tagging; Named entity recognition; Statistical machine translation; Natural language processing; Smart cities;
• ISBN/ISSN: 2046-6099
• URL: https://doi.org/10.1108/SASBE-03-2019-0031
• Abstract:
  The purpose of this paper is to present a system based on deep neural networks to extract particular entities from natural language text, knowing that a massive amount of textual information is electronically available at present. Notably, a large amount of electronic text data indicates great difficulty in finding or extracting relevant information from them. This study presents an original system to extract Arabic-named entities by combining a deep neural network-based part-of-speech tagger and a neural network-based named entity extractor. Firstly, the system extracts the grammatical classes of the words with high precision depending on the context of the word. This module plays the role of the disambiguation process. Then, a second module is used to extract the named entities. Using deep neural networks in natural language processing, requires tuning many hyperparameters, which is a time-consuming process. To deal with this problem, applying statistical methods like the Taguchi method is much requested. In this study, the system is successfully applied to the Arabic-named entities recognition, where accuracy of 96.81 per cent was reported, which is better than the state-of-the-art results. The system is designed and trained for the Arabic language, but the architecture can be used for other languages. Information extraction systems are developed for different applications, such as analysing newspaper articles and databases for commercial, political and social objectives. Information extraction systems also can be built over an information retrieval (IR) system. The IR system eliminates irrelevant documents and paragraphs. The proposed system can be regarded as the first attempt to use double deep neural networks to increase the accuracy. It also can be built over an IR system. The IR system eliminates irrelevant documents and paragraphs. This process reduces the mass number of documents from which the authors wish to extract the relevant information using an information extraction system.

Sahebzadeh, S, Dalvand, Z, Sadeghfar, M and Heidari, A (2018) Vernacular architecture of Iran’s hot regions; elements and strategies for a comfortable living environment. Smart and Sustainable Built Environment, 9(04), 573–93.

Susilo, A, Fitriah, F, Sunaryo, Ayu Rachmawati, E T and Suryo, E A (2020) Analysis of landslide area of Tulung subdistrict, Ponorogo, Indonesia in 2017 using resistivity method. Smart and Sustainable Built Environment, 9(04), 341–60.

Tunji-Olayeni, P, Kajimo-Shakantu, K and Osunrayi, E (2020) Practitioners' experiences with the drivers and practices for implementing sustainable construction in Nigeria: a qualitative assessment. Smart and Sustainable Built Environment, 9(04), 443–65.

van Stijn, A and Gruis, V (2020) Towards a circular built environment. Smart and Sustainable Built Environment, 9(04), 635–53.