| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560777 |
| ISSN: | 1405-5546 |
| Autores: | Soto de la Cruz, Ramón1 Castro Espinoza, Félix Agustín2 Soto, Liz1 |
| Instituciones: | 1Universidad de Sonora, Departamento de Contabilidad, Hermosillo, Sonora. México 2Universidad Autónoma del Estado de Hidalgo, Centro de Investigación en Tecnologías de Información y Sistemas, Pachuca, Hidalgo. México |
| Año: | 2023 |
| Periodo: | Ene-Mar |
| Volumen: | 27 |
| Número: | 1 |
| Paginación: | 173-182 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | Massive amounts of data are generated every day from all kinds of sources, from numerical data generated by sensors to veiled messages on social networks. Transforming these data into properly organized pieces of information and transforming it into resources for decision-making is complicated, not only because of the speed and volume at which it is produced, but due to the fact the high complexity of the context in which it is generated. Often, the first step in analyzing the data is to separate it into categories that correspond to segments of interest in that context. However, in many real cases, the limits of these segments and even the number of existing segments is unknown. Clustering techniques allow defining the classes of entities in a data set with sufficient relevance. However, those techniques usually work only with numerical data. Surveys are a very useful tool for collecting data in ill-defined contexts, but these data usually contain values that are not only numerical but of a very diverse nature. This paper presents a modification to the Isodata method to process data with mixed numerical and categorical values. The resulting algorithm is tested by analyzing the results of the 2021 Stack Overflow developer survey. The results obtained in the clustering of such data are sound and show that the Isodata method, with the proposed adaptations, can be successfully employed to discover patterns in complex mixed data. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Procesamiento de datos |
| Keyword: | Data processing |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
