[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118864-en":3,"doc-seo-118864-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118864,8796095360427,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Machine Learning Algorithms applied in a Service Platform for Professional Services Case Study","This paper proposes implementation alternatives for a marketplace named “Clic”, focusing on the technological infrastructure required to operate with machine learning algorithms. User research was conducted with two groups, clients and professionals, to assess intended use and the likelihood of payment for publishing services. The work defines recommended steps for building Clic, describes how training data is collected from users, and identifies suitable development environments. It also reports survey results and evaluates the feasibility and financial viability of the machine learning approach for project execution.","Universidad de Lima Facultad de Ingeniería Carrera de Ingeniería Industrial  \nMACHINE LEARNING ALGORITHMS APPLIED IN A SERVICE PLATFORM FOR PROFESSIONAL SERVICES CASE STUDY  \nTesis para optar el Título Profesional de Ingeniero Industrial  \nRenato Alejandro Manrique Acha Código 20121923  \nRoger Elias Lescano Vargas  \nCódigo 20120714  \nAsesor  \nJosé Antonio Taquía Gutiérrez  \nLima – Perú  \nSetiembre de 2023  \nMachine Learning Algorithms applied in a Service Platform for Professional Services Case  \nStudy  \nRenato Alejandro Manrique Acha  \nUniversidad de Lima, Carrera de Ingeniería Industrial Lima, Perú  \n[20121923@aloe.ulima.edu.pe](20121923@aloe.ulima.edu.pe)  \nRoger Elías Lescano Vargas  \nUniversidad de Lima, Carrera de Ingeniería Industrial Lima, Perú  \n[rogerlescanov@gmail.com](rogerlescanov@gmail.com)  \nJosé Antonio Taquía Gutiérrez  \nUniversidad de Lima, Instituto de Investigación Científica, Carrera de Ingeniería Industrial.  \nLima, Perú  \n[jtaquia@ulima.edu.pe](jtaquia@ulima.edu.pe)  \nAbstract  \nThis paper presents alternatives for the implementation of a Market Place called “Clic”, considering the technological infrastructure necessary for its operation based on Machine Learning algorithms. During the elaboration of this paper, surveys were conducted to both users qualified as \"Clients\" and \"Professionals\"about the intentionality of use and the probability of payment for the publication of their services in the platform. This paper presents the recommended steps for the composition of the Clic company, the way the information is collected for Machine Learning and the data obtained from the users, the recommended environments for the development of the application, the results of the surveys carried out, the feasibility of the Machine Learning algorithm, numerical data of financial feasibility for the execution of the project.  \nKey words  \nDigital Transformation, Professionals, Machine Learning, Marketplace, Service Platform.  \n1. Introduction  \nIn Peru, there is still no web-based portal of professionals and technicians that allows direct contact with customers who need services ranging from psychological care, math classes, legal guidance or even requesting home repairs.  \nFor this reason, the present research describes a technological solution for a Marketplace where a search can be made among options of professionals, comparing prices and qualifications, making the payment online and coordinating the attention of the service in a virtual way. Likewise, the Marketplace \"Clic\"referred to above, will allow professionals to have greater visibility and opportunity to offer their services in a reliable, safe and easy way. The functioning of the Marketplace will be powered by preference algorithms that use machine learning to make personalized recommendations for both clients and professionals considering aspects such as score, location, need or interest.  \nThe importance of this project is that it can help reduce the unemployment gap in metropolitan Lima , currently estimated at 443,600 people and increase the income of professionals according to the (INEI National Institute of Statistics and Informatics 2023) .  \n1.1 Objectives  \nOverall objective  \nTo give visibility to the potential reception of a marketplace in the Lima market where qualified professional services are offered.  \nSpecific objetives  \n● Present a recommendation system that could be considered to match requirements and profiles considering Machine Learning algorithms.  \n● Establish implementation costs for the project, as well as sources of income to make the project viable in the Peruvian market.  \n2. Literature Review  \nThe authors Cañazaka, et al. (2018) details how a virtual platform for independent professionals and small business can generate revenue outside regular working hours. Among the categories of all professional could be graphic design, translation, web programming, digital marketing, technology equipment maintenance, legal, accounting and","cbCaiiXDGxsZBKZq","https://ap.wps.com/l/cbCaiiXDGxsZBKZq","pdf",733892,1,14,"English","en",105,"# Introduction\n## Objectives\n# Literature Review","[{\"question\":\"What problem does the Clic marketplace aim to solve in Peru?\",\"answer\":\"It addresses the lack of a web-based portal connecting customers with professionals and technicians across services such as education, legal guidance, psychological care, and home repairs.\"},{\"question\":\"How will Clic personalize recommendations using machine learning?\",\"answer\":\"Clic will use preference algorithms that apply machine learning to recommend options to clients and professionals based on factors such as score, location, needs, and interests.\"},{\"question\":\"What research inputs are used to support feasibility and financial analysis?\",\"answer\":\"The study uses surveys from clients and professionals to capture intended use and payment probability, and then combines the survey results with data to assess the algorithm’s feasibility and the project’s financial viability.\"}]","Machine Learning Algorithms applied in a Service Platform for Professional Services Case Study | 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