Examinando por Autor "Pucuhuayla-Revatta, Félix"

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  • Miniatura
    PublicaciónAcceso abierto
    “Digital Tool for Film Promotion Through the Use of Augmented Reality“
    (International Association of Online Engineering, 2023-01) Beltozar-Clemente, Saul; Sierra-Liñan, Fernando; Pucuhuayla-Revatta, Félix; Zapata-Paulin, Joselyn; Cabanillas-Carbonell, Michael
    “After the isolation caused by the pandemic, the entertainment sector has been forced to change the way it markets its products and services, and users have been adapting to the change. The objective of this research article is to provide added value and innovation to the advertising promotions of movies in the premiere, through the development of a mobile application based on augmented reality to improve customers’ shopping experience. For which the Agile Mobile-D Methodology was used for the development of the application and the results were studied using 5 indicators: Time to choose a movie, where an improvement of 38.26% was obtained compared to the Pre-Test; regarding the indicator time to acquire information about the movie, an improvement of 81.33% was obtained. 33%; concerning the third indicator, time to initiate the purchase, an improvement of 88% was obtained; concerning the fourth indicator, time to obtain a reminder, an improvement of 83.33% was obtained, making the time with the use of the application shorter; finally, concerning the customer satisfaction indicator, 73% of the users who used the application rated their experience as between satisfied and very satisfied.“
  • Miniatura
    PublicaciónAcceso abierto
    “Search and classify topics in a corpus of text using the latent dirichlet allocation model“
    (Institute of Advanced Engineering and Science, 2022-11-18) Iparraguirre-Villanueva, Orlando; Sierra-Liñan, Fernando; Herrera Salazar, Jose Luis; Beltozar-Clemente, Saul; Pucuhuayla-Revatta, Félix; Zapata-Paulin, Joselyn; Cabanillas-Carbonell, Michael
    “This work aims at discovering topics in a text corpus and classifying the most relevant terms for each of the discovered topics. The process was performed in four steps: first, document extraction and data processing; second, labeling and training of the data; third, labeling of the unseen data; and fourth, evaluation of the model performance. For processing, a total of 10,322 ““curriculum““ documents related to data science were collected from the web during 2018-2022. The latent dirichlet allocation (LDA) model was used for the analysis and structure of the subjects. After processing, 12 themes were generated, which allowed ranking the most relevant terms to identify the skills of each of the candidates. This work concludes that candidates interested in data science must have skills in the following topics: first, they must be technical, they must have mastery of structured query language, mastery of programming languages such as R, Python, java, and data management, among other tools associated with the technology.“