scholarly journals Research on Deep Learning-Based Algorithm and Model for Personalized Recommendation of Resources

2022 ◽  
Vol 2146 (1) ◽  
pp. 012007
Author(s):  
Yu’e Liu

Abstract Resource recommendation system is a new type of management system, which uses personalized information to solve business needs such as customer consultation and product recommendation, and provides users with high quality services and achieves accurate marketing, so nowadays resource recommendation system has a pivotal role in modern resource management. In this paper, I study the algorithm and model of resource personalized recommendation based on deep learning, taking human resource recommendation as an example.

Author(s):  
Kristian Adi S. ◽  
Suhatati Tjandra ◽  
S.T.B. Tambunan

Pengelolaan sumber daya manusia merupakan salah satu faktor utama dalam pengembangan suatu perusahaan. Pengaturan Sumber daya manusia pada sebuah perusahaan sangatlah rumit dan membutuhkan ketelitian. Untuk itu diperlukan suatu sistem yang dapat membantu tugas HRD pada perusahaan yang disebut Human resource Management System (HRM System).  Kesalahan yang kecil pada pengaturan sumber daya manusia pada perusahaan akan berakibat fatal terutama pengaturan yang berhubungan dengan anggaran atau biaya. Penggaturan angaran untuk sumber daya manusia membutuhkan bantuan dalam hal pencatatan maupun sistem yang akurat sehingga tidak ada kesalahan dan celah yang merugikan pihak perusahaan dan pegawai. Perancangan Website ini, bertujuan untuk  mengembangkan sistem Human Resource Administration dengan menggunakan jaringan intranet. Pembuatan akan dibantu dengan kerangka kerja untuk pembuatan website yang bernama Laravel guna memudahkan pembuatan serta pengembangan website kedepanya. Website ini juga dilengkapi dengan database MySql dan Semantic UI sebagai tampilan utama website


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Zhan Shi ◽  
Wei Wang

Swimming is not only an entertaining hobby but also a sporting event. It is a sport for strengthening the body. Although there are many swimming coaches, there are different swimming teaching courses. However, choosing the right swimming instructor or course is the motivation for learning swimming activities. To this end, this paper conducts related research on the personalized recommendation system for swimming teaching based on deep learning with the purpose of improving the accuracy of the recommendation system to meet the needs of the users and promote the development of swimming events. This article mainly uses the experimental test method, the system construction method, and the questionnaire survey method to analyze and study the personalized swimming teaching system and the students’ attitude to it and draw a conclusion finally. The data results show that the accuracy of the system designed in this paper can meet the basic requirements. Hence, it can bring an excellent experience to the users. According to the questionnaire data, 85%–95% of people have great confidence in the personalized recommendation system.


2020 ◽  
Vol 8 (3) ◽  
pp. 0-0
Author(s):  
Mohammad Javadipour ◽  
Mohammad Hashemi Siyavoshani ◽  
Mohammad Hossein Ghorbani ◽  
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Kybernetes ◽  
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Min Zhao ◽  
Kamran Rabiei

PurposeThe present study is descriptive research in terms of purpose, descriptive analysis in terms of nature and cross-sectional research in terms of time. The study’s statistical population includes all employees and managers of the China City Organization selected as sample members using random sampling method and Krejcie table of 242 people. The questionnaire was modified and revised based on the goals, tasks and mission of the target organization to collect information. In data analysis, due to the normality of data distribution, the structural equation modeling method is used to evaluate the causal model, reliability and validity of the measurement model. Evaluation and validation of the model are done through the structural equation model. Questionnaire-based model and data are analyzed using Smart PLS 3.0. The main purpose of this study is to assess the feasibility of implementing the human resource payroll management system based on cloud computing technology.Design/methodology/approachNew technologies require innovative approaches for creating valuable opportunities in an organization to integrate the physical flows of goods and services and financial information. Today, cloud computing is an emerging mechanism for high-level computing as a storage system. It is used to connect to network hosts, infrastructure and applications and provide reliable services. Due to advances in this field, cloud computing is used to perform operations related to human resources. The role, importance and application of cloud computing in human resource management, such as reducing the cost of hardware and information software in hiring, job planning, employee selection, employee socialization, payroll, employee performance appraisal, rewards, etc., is raised. This way, human resource management teams can easily view resumes, sort candidates and observe and analyze their performance. Cloud computing is effective in implementing human resource payroll management systems. Therefore, the primary purpose of this study is to assess the feasibility of implementing the human resource payroll management system based on cloud computing technology.FindingsTesting the research hypotheses shows that the dimension desirability of ability and acceptance is provided in dimensions related to the minimum conditions required to implement cloud computing technology in the organization. For this reason, the feasibility of implementing the systems based on cloud computing in companies must be considered.Research limitations/implicationsThis study also has some limitations that need to be considered in evaluating the results. The study is limited to one region. It cannot be assured that the factors examined in other areas are effective. The research design for this study is a cross-sectional study. It represents the static relationship between the variables. Since cross-sectional data from variable relationships are taken at a single point in time, they are collected in other periods. As a proposal, future researchers intend to investigate the impact of Enterprise Resource Planning (ERP) systems based on cloud computing.Practical implicationsThe research also includes companies, departments and individuals associated with systems based on cloud computing.Originality/valueIn this paper, the feasibility of implementing the human resource payroll management system based on cloud computing is pointed out, and the approach to resolve the problem is applied to a practical example. The presented model in this article provides a complete framework to investigate the feasibility of implementing the human resource payroll management system based on cloud computing.


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