scholarly journals TEXT MINING-BASED PATENT ANALYSIS OF BIM APPLICATION IN CONSTRUCTION

2021 ◽  
Vol 27 (5) ◽  
pp. 303-315
Author(s):  
Xing Pan ◽  
Botao Zhong ◽  
Xiaobo Wang ◽  
Ran Xiang
Keyword(s):  
Network Analysis ◽  
Text Mining ◽  
Latent Dirichlet Allocation ◽  
Technological Development ◽  
Quantitative Characteristic ◽  
Citation Network ◽  
Development Trend ◽  
Patent Analysis ◽  
Information Modeling ◽  
Characteristic Analysis

As a data tool applicable to the full life-cycle of construction engineering and management, Building Information Modeling (BIM) has great potential for significantly increasing project productivity and performance. Awareness of BIM application hotspots and forecasting its trends can drive innovations in construction field. Using patents as data resources, this study develops an effective framework integrating the citation network analysis and the topic clustering technology to identify BIM application information and forecast its trends. This framework comprises three-step analysis:(1) quantitative characteristic analysis of patent outputs; (2) Social Network Analysis (SNA)-based co-occurrence network analysis; and (3) identification of BIM topics using a Latent Dirichlet Allocation (LDA). Finally, the case demonstrates the effectiveness of this framework contributing to promote technological development and innovation of BIM. The contributions of this study are threefold: (1) an innovative text mining-based framework for BIM patent analysis in construction is developed; (2) patents that have focused on identifying the application hotspots and development trend of BIM in accordance with our developed framework are reviewed; and (3) a signpost for technological development and innovation of BIM is provided.

scholarly journals Text Mining and Citation Network of Ecosystem Services Publications

2019 ◽  
Author(s):  
Muhammad Malik Ar-Rahiem
Keyword(s):  
Ecosystem Services ◽  
Network Analysis ◽  
Text Mining ◽  
Biodiversity Conservation ◽  
Bibliometric Analysis ◽  
Natural Capital ◽  
Citation Network ◽  
Well Being ◽  
Bibliographic Coupling ◽  
Citation Network Analysis

Ecosystem Services is an important concept to achieve Sustainable Development Goals 2030. For the past 20 years, this concept has grown exponentially and the metadata of these publications can be considered as big data. A bibliometric analysis was conducted to Ecosystem Services publications from Web of Science database, which are text-mining analysis, bibliographic coupling, and citation network analysis. Text-mining analysis results were a cluster map of keywords representing the content of abstract and title from 4203 publications in the dataset. Bibliographic coupling analysis results were a cluster of documents which analyzed using natural language processing to extract the main idea of the documents. Using these two analysis insight about ecosystem services are obtained. Ecosystem services in general can be divided into 6 big clusters: economic assessment of ecosystem services as natural capital, ecosystem services assessment in term of accounting and management, biodiversity conservation in term of species richness, biodiversity conservation in term of human well-being, climate change and ecosystem services, and ecosystem services in urban area. Finally, citation network analysis was performed. 5700 publications consist of publications from the dataset and cited references from the publications were analyzed and 50 most influential articles from 1977 to 2018 with highest citation score was plotted in chronological order, providing insight on how the topic has been developing over time and important publications to be read. Bibliometric analysis proved to be very useful, especially as the preliminary step before conducting literature review. This technique can be very beneficial for early career scientists who wanted to recognize a field of science or wanted to know the research gaps that could be worked on.

scholarly journals Patent Analysis in the 5G Network

2021 ◽  
Vol 29 (6) ◽  
pp. 1-28
Author(s):  
Hui Eva Zhang ◽  
Kok Hoe Wong ◽  
Victor Chang
Keyword(s):  
Hot Spots ◽  
Citation Network ◽  
Development Trend ◽  
The United States ◽  
Patent Analysis ◽  
Patent Data ◽  
Index Analysis ◽  
Critical Nodes ◽  
5G Network ◽  
Overview Analysis

In recent years, 5G has been the focus of research and development in the telecom industry. This paper aims to understand the development trend and technical hot spots of 5G technology through the patent analysis and build a citation network at the assignee organization level. The workflow of the paper is divided into four steps: patent data collection and cleaning, patent overview analysis, network creation and analysis, O-I index analysis. This article collected the patent data from the United States patent and trademark office (USPTO). We understand the application trend, technical hot spots, and leading players in the 5G domain through the patent overview analysis. We comprehend the structure and characteristics of the network and critical nodes from network topology analysis. By using O-I index analysis, we learn the flow of 5G technology knowledge between the organizations. This paper provides a useful analytical model for the patent analysis and technological knowledge flow in a specific field, which can be applied to patent analysis in other fields.

scholarly journals Study on Horizon Scanning by Citation Network Analysis and Text Mining: A Focus on Drug Development Related to T Cell Immune Response

2021 ◽  
Author(s):  
Erika Fujii ◽  
Takuya Takata ◽  
Hiroko Yamano ◽  
Masashi Honma ◽  
Masafumi Shimokawa ◽  
...  
Keyword(s):  
Network Analysis ◽  
Text Mining ◽  
Product Development ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Citation Network ◽  
Research Trends ◽  
Horizon Scanning ◽  
Scientific Papers ◽  
Citation Network Analysis

AbstractCertain innovative technologies applied to medical product development require novel evaluation approaches and/or regulations. Horizon scanning for such technologies will help regulators prepare, allowing earlier access to the product for patients and an improved benefit/risk ratio. This study investigates whether citation network analysis and text mining of scientific papers could be a tool for horizon scanning in the field of immunology, which has developed over a long period, and attempts to grasp the latest research trends. As the result of the analysis, the academic landscape of the immunology field was identified by classifying 90,450 papers (obtained from PubMED) containing the keyword “immune* and t lymph*” into 38 clusters. The clustering was indicative of the research landscape of the immunology field. To confirm this, immune checkpoint inhibitors were used as a retrospective test topic of therapeutics with new mechanisms of action. Retrospective clustering around immune checkpoint inhibitors was found, supporting this approach. The analysis of the research trends over the last 3 to 5 years in this field revealed several candidate topics, including ARID1A gene mutation, CD300e, and tissue resident memory T cells, which shows notable progress and should be monitored for future possible product development. Our results have demonstrated the possibility that citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of life science fields such as immunology.

Development trend forecasting for coherent light generator technology based on patent citation network analysis

2017 ◽  
Vol 111 (1) ◽  
pp. 297-315 ◽  
Author(s):  
Hanlin You ◽  
Mengjun Li ◽  
Keith W. Hipel ◽  
Jiang Jiang ◽  
Bingfeng Ge ◽  
...  
Keyword(s):  
Network Analysis ◽  
Citation Network ◽  
Development Trend ◽  
Patent Citation ◽  
Coherent Light ◽  
Citation Network Analysis ◽  
Trend Forecasting ◽  
Patent Citation Network

scholarly journals Patent analysis in the 5G network

2021 ◽  
Vol 29 (6) ◽  
pp. 0-0
Keyword(s):  
Hot Spots ◽  
Citation Network ◽  
Development Trend ◽  
The United States ◽  
Patent Analysis ◽  
Patent Data ◽  
Index Analysis ◽  
Critical Nodes ◽  
5G Network ◽  
Overview Analysis

In recent years, 5G has been the focus of research and development in the telecom industry. This paper aims to understand the development trend and technical hot spots of 5G technology through the patent analysis and build a citation network at the assignee organization level. The workflow of the paper is divided into four steps: patent data collection and cleaning, patent overview analysis, network creation and analysis, O-I index analysis. This article collected the patent data from the United States patent and trademark office (USPTO). We understand the application trend, technical hot spots, and leading players in the 5G domain through the patent overview analysis. We comprehend the structure and characteristics of the network and critical nodes from network topology analysis. By using O-I index analysis, we learn the flow of 5G technology knowledge between the organizations. This paper provides a useful analytical model for the patent analysis and technological knowledge flow in a specific field, which can be applied to patent analysis in other fields.

scholarly journals Study on Horizon Scanning with a Focus on the Development of AI-Based Medical Products: Citation Network Analysis

2021 ◽  
Author(s):  
Takuya Takata ◽  
Hajime Sasaki ◽  
Hiroko Yamano ◽  
Masashi Honma ◽  
Mayumi Shikano
Keyword(s):  
Network Analysis ◽  
Text Mining ◽  
Citation Network ◽  
Research Progress ◽  
Research Trend ◽  
Medical Products ◽  
Medical Technologies ◽  
Horizon Scanning ◽  
Citation Network Analysis ◽  
Clinical Records

AbstractHorizon scanning for innovative technologies that might be applied to medical products and requires new assessment approaches to prepare regulators, allowing earlier access to the product for patients and an improved benefit/risk ratio. The purpose of this study is to confirm that citation network analysis and text mining for bibliographic information analysis can be used for horizon scanning of the rapidly developing field of AI-based medical technologies and extract the latest research trend information from the field. We classified 119,553 publications obtained from SCI constructed with the keywords “conventional,” “machine-learning,” or “deep-learning" and grouped them into 36 clusters, which demonstrated the academic landscape of AI applications. We also confirmed that one or two close clusters included the key articles on AI-based medical image analysis, suggesting that clusters specific to the technology were appropriately formed. Significant research progress could be detected as a quick increase in constituent papers and the number of citations of hub papers in the cluster. Then we tracked recent research trends by re-analyzing “young” clusters based on the average publication year of the constituent papers of each cluster. The latest topics in AI-based medical technologies include electrocardiograms and electroencephalograms (ECG/EEG), human activity recognition, natural language processing of clinical records, and drug discovery. We could detect rapid increase in research activity of AI-based ECG/EEG a few years prior to the issuance of the draft guidance by US-FDA. Our study showed that a citation network analysis and text mining of scientific papers can be a useful objective tool for horizon scanning of rapidly developing AI-based medical technologies.

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