scholarly journals DEVELOPING A TEXT MINING TECHNIQUE TO IDENTIFY CONCERTED OR OPPOSED RELATIONS AMONG COMMITTEE MEMBERS IN PUBLIC WORK PLANNING PROCESSES WITH USING THE PROCESSES' MINUTES

2014 ◽  
Vol 70 (6) ◽  
pp. II_249-II_256
Author(s):  
Asako IWAMI ◽  
Tomohiko OHNO ◽  
Michinori KIMURA ◽  
Shinji IDE
Keyword(s):  
Text Mining ◽  
Mining Technique ◽  
Public Work ◽  
Planning Processes ◽  
Work Planning

Evaluation of Universities' Integrated Reports Using Text Mining Technique

2021 ◽  
Author(s):  
Takumi Miura ◽  
Takumi Furukawa ◽  
Junko Harada ◽  
Yudai Hirano ◽  
Takako Hashimoto
Keyword(s):  
Text Mining ◽  
Mining Technique

Simulation-Based Work Plan Verification in Shipyards

2014 ◽  
Vol 30 (02) ◽  
pp. 49-57
Author(s):  
Dong Kun Lee ◽  
Jong Gye Shin ◽  
Youngmin Kim ◽  
Yong Kuk Jeong
Keyword(s):  
Production Management ◽  
Limited Resources ◽  
Management Systems ◽  
Application System ◽  
High Productivity ◽  
Work Plan ◽  
Simulation Based ◽  
Planning Processes ◽  
Work Planning ◽  
Production Plans

The productivity of a shipyard depends on how efficiently and systematically its limited resources are managed and used. Korean shipyards, the most competitive in the world, have developed and operate their own production management systems to attain high productivity, each of which reflects the unique characteristics of a specific company. Recently, research on simulation methods to enhance production management systems has been gaining popularity. Production management based on simulations rejects decision-making based on experience and intuition and values the establishment of improvement methods based on quantitative and concrete data. In this article, simulation is applied to the work plan as part of the production planning in shipyards. To this end, the work planning processes and planning systems are analyzed. Based on this analysis, a simulation model and application system are suggested. By using the results obtained in this study, it is expected that shipyards can construct cycles for establishing, simulating, and analyzing work plans, enabling the establishment of more precise production plans.

The Effects of the State of Union Address of USA Presidents to Their Performance Ratings

2015 ◽  
Vol 3 (2) ◽  
pp. 1-12
Author(s):  
Carl Lee
Keyword(s):  
Text Mining ◽  
Performance Ratings ◽  
Presidential Approval ◽  
Approval Ratings ◽  
Mining Technique ◽  
State Of The Union ◽  
Speech Patterns ◽  
Modeling Techniques ◽  
Presidential Approval Ratings

In this article, the authors conduct a case study using text mining technique to analyze the patterns of the president's State of the Union Address in USA, and investigate the effects of these speech patterns on their performance rating in the following year. The speeches analyzed include the recent four USA presidents, Bush (1989 – 1992), Clinton (1993 - 2000), G.W. Bush (2001 – 2008), and Obama (2009 – 2011). The patterns found are further integrated and merged with over 4000 surveys on the presidents' performance ratings from 1989 to 2010. Two text mining methodology are applied to study the text patterns. Two predictive modeling techniques are applied to study the effects of these found patterns to their presidential approval ratings. The results indicate that the speech patterns found are highly associated with their approval rates.

Looking beyond the stars: A description of text mining technique to extract latent dimensions from online product reviews

2019 ◽  
Vol 62 (2) ◽  
pp. 195-215
Author(s):  
Frederik Situmeang ◽  
Nelleke de Boer ◽  
Austin Zhang
Keyword(s):  
Text Mining ◽  
Customer Satisfaction ◽  
Research Methodology ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Product Reviews ◽  
Marketing Literature ◽  
Mining Technique ◽  
Online Product Reviews ◽  
The Relationship

The purpose of this study is to contribute to the marketing literature and practice by describing a research methodology to identify latent dimensions of customer satisfaction in product reviews, and examining the relationship between these attributes and customer satisfaction. Previous research in product reviews has largely relied only on quantitative ratings, either stars or review score. Advanced techniques for text mining provide the opportunity to extract meaning from customer online reviews. By analyzing 51,110 online reviews for 1,610 restaurants via latent Dirichlet allocation, this study uncovers 30 latent dimensions that are determinants of customer satisfaction. Furthermore, this study developed measurements of sentiment and innovativeness as moderators of the effect of these latent attributes to satisfaction.

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