Towards an AEC-AI Industry Optimization Algorithmic Knowledge Mapping: An Adaptive Methodology for Macroscopic Conceptual Analysis
نویسندگان
چکیده
The Architecture, Engineering, and Construction (AEC) Industry is one of the most important productive sectors, hence also produce a high impact on economic balances, societal stability, global challenges in climate change. Regarding its adoption technologies, applications processes recognized by status-quo, slow innovation pace, conservative approaches. However, new technological era - 4.0 fueled AI- driving sectors highly pressurized competition sociopolitical landscape. In this paper, we develop an adaptive approach to mining text content literature research corpus related AEC AI (AEC-AI) industries, particular relation applications. We present first stage assessment algorithms, form integrative platform industry, AEC-AI industry 4.0. At stage, macroscopic method deployed characterize “Optimization,” key term using mixed methodology incorporating machine learning classical evaluation process. Our results show that effective use metadata, constrained search queries, domain knowledge allows getting target concept. This extraction high-level mapping conceptual structure characterization corpus. are comparable, at level, methodologies for review. addition, our designed incorporate further stages.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2021.3102215