Text mining of industry 4.0 job advertisements

Pejić-Bach, Mirjana; Bertoncel, Tine; Meško, Maja; Krstić, Živko

doi:10.1016/j.ijinfomgt.2019.07.014

Cited by 156 publications

(95 citation statements)

References 57 publications

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“…Recently, Pejic-Bach et al [201] applied text mining on publicly accessible job advertisements on LinkedIn-one of the most influential social media networks for business-and developed a profile of Industry 4.0 job advertisements.…”

Section: Other Social Media Platformsmentioning

confidence: 99%

Text Mining in Big Data Analytics

Hassani

Beneki

Unger

et al. 2020

BDCC

150

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Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by examining the developments within published literature over past years and provide valuable insights for practitioners and researchers on the predominant trends, methods, and applications of text mining research. In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, across a broad range of application areas are also investigated. Additionally, the benefits and challenges related to text mining are also briefly outlined.

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Section: Other Social Media Platformsmentioning

confidence: 99%

Text Mining in Big Data Analytics

Hassani

Beneki

Unger

et al. 2020

BDCC

150

View full text Add to dashboard Cite

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“…In the new digital divide, Industry 4.0 will play an important role for individuals, in that routine jobs are likely to be replaced by those requiring analytical skills, flexibility in decision making, and training in certain topics, such as trajectory data mining, text mining, and machine learning, as proved by many recent surveys on Industry 4.0 employment demands, for example, in Bach et al [206] and Fareri et al [207]. Regardless of the social skill requirements of Industry 4.0 job positions, trajectory data mining is of educational advancement from a technical perspective.…”

Section: Trajectory Data Mining In Industry 40mentioning

confidence: 99%

Big Trajectory Data Mining: A Survey of Methods, Applications, and Services

Wang

Miwa

Morikawa

2020

Sensors

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The increasingly wide usage of smart infrastructure and location-aware terminals has helped increase the availability of trajectory data with rich spatiotemporal information. The development of data mining and analysis methods has allowed researchers to use these trajectory datasets to identify urban reality (e.g., citizens’ collective behavior) in order to solve urban problems in transportation, environment, public security, etc. However, existing studies in this field have been relatively isolated, and an integrated and comprehensive review is lacking the problems that have been tackled, methods that have been tested, and services that have been generated from existing research. In this paper, we first discuss the relationships among the prevailing trajectory mining methods and then, classify the applications of trajectory data into three major groups: social dynamics, traffic dynamics, and operational dynamics. Finally, we briefly discuss the services that can be developed from studies in this field. Practical implications are also delivered for participants in trajectory data mining. With a focus on relevance and association, our review is aimed at inspiring researchers to identify gaps among tested methods and guiding data analysts and planners to select the most suitable methods for specific problems.

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“…It should be noted that several job profiles such as information and digitization/digitalization engineer, big data analyst, data scientist, machine learning engineer, and cloud services experts, did not exist ten years ago [31]. This is also attested in a recent analysis of Industry 4.0 related job profiles [32]. Enabling the workforce to acquire the required knowledge [33] and skills to respond to challenges and expectations of the industry when implementing the Industry 4.0, as well as migrating legacy industrial systems into Industry 4.0compliant systems are seen as vital.…”

Section: A Education New Skills and Job Profilesmentioning

confidence: 99%

“…Lifelong learning is seen as crucial here, since due to the rapid advances in hardware but mostly in software, the acquired knowledge quickly becomes obsolete and needs to be kept pertinent. The job profiles requested for Industry 4.0 related tasks show a mixture of soft skills and diverse technical expertise in new technologies [32]. Education aims to prepare the professionals for today's jobs rather than for ones of the future [38] since it is difficult to determine what will be tomorrow's jobs.…”

Section: A Education New Skills and Job Profilesmentioning

confidence: 99%

Quo Vadis Industry 4.0? Position, Trends, and Challenges

Leitão

Pires

Karnouskos

et al. 2020

IEEE Open J. Ind. Electron. Soc.

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Industry 4.0 vision and its mandated digital transformation are radically reshaping the way business is carried out and the way overall industrial processes and collaborations are operating. In this work, the objective is to analyze the current level of adoption of Industry 4.0, via the footprint available in industrial and academic research works. The analysis performed reveals insights on how Industry 4.0 has impacted and is still influencing research and innovation in industrial systems, services, and business approaches. It also reveals pertinent trends on key enabling features, technologies and challenges associated with this 4 th industrial revolution, mainly focusing on the pathways for wider industrial adoption of Industry 4.0-compliant technologies and solutions.

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Text mining of industry 4.0 job advertisements

Cited by 156 publications

References 57 publications

Text Mining in Big Data Analytics

Text Mining in Big Data Analytics

Big Trajectory Data Mining: A Survey of Methods, Applications, and Services

Quo Vadis Industry 4.0? Position, Trends, and Challenges

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