This paper aims to understand the characteristics of domestic big data jobs requirements through k-means text clustering, help enterprises, and employees to identify big data talents, and promote the further development of big data-related research. Firstly, the crawler software is used to crawl the recruitment information about "big data" on the zhaopin.com recruitment website. Then, Jieba word segmentation and K-means text clustering are used to cluster big data recruitment positions, and the number of clustering was determined by the average sum of squares within the group. Finally, big data jobs are divided into 10 categories, and the urban distribution, salary level, education requirements, and experience requirements of big data jobs are discussed and analyzed from the perspectives of the overall data set and clustering results, to clarify the characteristics of big data job demands. The analysis results show that the job demands of big data are mainly distributed in first-tier cities and new first-tier cities. Enterprises are more inclined to job seekers with a college degree or bachelor’s degree and more than one year’s relevant experience. There are wage differences among different types of jobs. The higher the position, the higher the requirement for education and experience will be.
ObjectivesProtein post-translational modifications (PTMs) are closely associated with tumorigenesis, targeting PTMs of key proteins might be the focus of antitumor drug discovery. This study aimed to analyze the research progress on protein PTMs in tumorigenesis by performing qualitative and quantitative evaluations.MethodsThe Web of Science Core Collection was selected as the database, and Science Citation Index Expanded was selected as the citation index. Visualization tools such as VOSviewer, CiteSpace, HistCite, and Online Analysis Platform of Bibliometrics were used to deeply explore the information of the retrieved research papers and analyze them in terms of research trends and main aspects of research.ResultsThe search yielded 3777 relevant articles. The results showed that the total number of PTMs related papers in cancer field has been increasing annually, with the largest number of papers published in the United States of America. The co-word cluster analysis showed that the research on PTMs and tumorigenesis was primarily focused on the following four areas, mechanism, histone, P53, key Technologies. Tumor metabolism, autophagy, and protein-protein interaction, histone ubiquitination have become new research topics.ConclusionThis study provides an important reference for the research direction and selection of topics of interest in the PTMs of cancer field.
Based on product lifecycle management (PLM) theory and social comparison theory, this paper constructs a performance ranking model of automobile product development project team members, uses an active server provider (ASP) to develop the system, realizes the online operation and real-time analysis of the performance management system, and solves the problems of the low efficiency, low morale and unfair assessment of product development team members caused by traditional performance assessment. The performance management platform for the team members of the automotive product development project uses a PLM system to realize a systematic and standardized list of project functions and provide a performance appraisal management system that can be evaluated and fairly compared for project team members. Based on the performance appraisal practice of automotive product development project team members of M Automotive Products Company, this study verified the feasibility of the ranking model’s transformation to work habits based on the predetermined and result data of the mission completion rate, the punctuality rate and the degree of improvement of the management level of product development project team. Through the tracking of the team performance ranking function, it is found that the model can solve the problems of untimely assessment and insufficient incentives in the current traditional performance appraisal, enhance the overall enthusiasm of the team, and give full play to the subjective initiative of the team.
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