Text Mining-Based Emerging Trend Analysis for the Aviation Industry

Abstract

meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future.Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results.On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

Analysis of Issues and Future Trends Impacting Drug Safety in South Korea

“…Unlike qualitative conventional methods such as Delphi, expert panels, and scenarios, which rely on opinions from experts, text-mining can forecast the future in objective and quantitative ways [43,44]. In addition, text-mining can save money and time when deriving trends as compared to costly and time-consuming literature reviews and experts’ advice [43,44]. A database of news websites about medicines in South Korea () was used.…”

The Analysis of Research Trends in Biometrics in South Korea

“…The relationship is visualized as a network which shows the connection between words by using lines-called a -link‖. The relationship between words is analyzed so that the meaning and importance of the words in the whole network can be grasped in the structural relation [12]- [13].…”

Developing a Methodology of Structuring and Layering Technological Information in Patent Documents through Natural Language Processing

“…In the method of using the occurrence frequency and the TF-IDF value, parts of the keywords are selected and analyzed by evaluating the importance of the keyword without using all the keywords appearing in the document. Kim et al [26] and Min et al [27] selected future promising areas by analyzing the time series of words appearing in papers, news, and policy research reports. Choi et al [2] predicted promising technologies by investigating the network of keywords.…”