Métricas de similaridad y evaluación para sistemas de recomendación de filtrado colaborativo

Olguin, Gustavo; Jesús, Yadira Laureano de; Herrero, María de la Concepción Pérez de Celis

doi:10.36825/riti.07.14.019

Cited by 4 publications

(5 citation statements)

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“…Se basan en predicciones hechas a partir de las valoraciones que los usuarios dan a los artículos, para poder filtrar información de acuerdo con sus los gustos y preferencias, mejorando la efectividad de las ventas y atrayendo la atención de más usuarios que buscan comprar según sus intereses (Belkhadir et al, 2019). Estos sistemas incluyen el hecho de que, cuanto más precisas sean las recomendaciones, el sitio recuerda quién es el usuario y qué le gusta, dándole así un sentido de pertenencia, mostrando el contenido de su preferencia y sin perder su atención (Mendoza Olguín et al, 2019).…”

Section: Sistema De Recomendaciónunclassified

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Una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos tecnológicos

Guevara Fernandez,

Coral Ygnacio

2023

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Los sistemas de recomendación son herramientas de filtrado de información que ayudan a presentar elementos a los usuarios en función de sus gustos y preferencias. Por ejemplo, pueden realizar sugerencias de artículos para el hogar o productos específicos para un usuario. Actualmente, existen diversos tipos de sistemas de recomendación (SR) para abordar el incremento de información en internet por parte de las empresas y, de esa manera, mejorar la eficiencia en sus procesos de venta de productos. Así mismo, existen diferentes tipos de sistemas de recomendación que utilizan técnicas específicas para cumplir con los objetivos del rubro de la empresa. Están los sistemas de popularidad, por ejemplo, que se centran en la popularidad de un producto, teniendo como criterios los likes, comentarios, el tiempo que un cliente se tomó para revisar el producto, etcétera. También existen los de contenido que, basándose en el historial de un cliente, intentan predecir qué busca el usuario y sugerir productos en relación a posibles gustos del cliente. Finalmente, los sistemas de recomendación de filtrado colaborativo, que generan recomendaciones analizando datos, identificando usuarios y comparando la información del perfil del usuario con la de un colectivo de usuarios. En base a lo antes mencionado, en el presente artículo de investigación se propone una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos eléctricos. El objetivo es apoyar y facilitar la toma de decisiones, así como también ayudar en el mejoramiento continuo de las empresas y, de esta manera, incrementar la eficiencia de los sistemas al momento de su implementación.

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Section: Sistema De Recomendaciónunclassified

“…También se encarga de evaluar las calificaciones de los productos y predecir cuáles podrían gustar al cliente (Tewari, 2020). Una de las deficiencias que presenta este sistema es que, si los usuarios no evalúan la mayor cantidad de ítems, la recomendación será imprecisa (Mendoza Olguín et al, 2019).…”

Section: Filtrado Colaborativounclassified

Una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos tecnológicos

Guevara Fernandez,

Coral Ygnacio

2023

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“…Furthermore, this logarithmic transformation allows you to create contour maps, with intervals based on a logarithmic scale, by filling the maps with a gradient with the same scale as the axes. Thus, it is possible to create accurate maps of the data set when these are extended in different orders of magnitude [47,48].…”

Section: Exploratory Data Analysismentioning

confidence: 99%

Ecosystem Services Assessment for Their Integration in the Analysis of Landslide Risk

et al. 2022

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Landslides are disasters that cause damage to anthropic activities, innumerable loss of human life, and affect the natural ecosystem and its services globally. The landslide risk evaluated by integrating susceptibility and vulnerability maps has recently become a manner of studying sites prone to landslide events and managing these regions well. Developing countries, where the impact of landslides is frequent, need risk assessment tools to address these disasters, starting with their prevention, with free spatial data and appropriate models. However, to correctly understand their interrelationships and social affection, studying the different ecosystem services that relate to them is necessary. This study is the first that has been attempted in which an integrated application methodology of ecosystem services is used to know in a systematic way if the information that ecosystem services provide is useful for landslide risk assessment. For the integration of ecosystem services into the landslide risk evaluation, (1) eight ecosystem services were chosen and mapped to improve understanding of the spatial relationships between these services in the Guerrero State (México), and (2) areas of synergies and trade-offs were identified through a principal component analysis, to understand their influence on risk analysis better. These are extracted from the models of the ARIES platform, artificial intelligence, and big data platform. Finally, (3) the similarity between the risk characteristics (susceptibility and vulnerability, already mapped by the authors) and the ecosystem services assessment was analysed. The results showed that the ecosystem services that most affect the synergy are organic carbon mass and the potential value of outdoor recreation; meanwhile, the possible removed soil mass was the most important trade-off. Furthermore, the lowest similarity value was found between landslide vulnerability and ecosystem services synergy, indicating the importance of including these ecosystem services as a source of valuable information in the risk analysis methodologies, especially with respect to risk vulnerability.

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“…Along with these recommender systems, there are other recommender systems based on hybrid methods [42][43][44], where they take as a reference the experiences of activities based on existing records. its execution, the subsystem uses visualization and fuzzy logic techniques to recommend the activities or educational resources to be used to improve the efficiency of the teaching-learning process.…”

Section: Recommender Systemsmentioning

confidence: 99%

Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries

et al. 2022

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Incorporating technology into virtual education encourages educational institutions to demand a migration from the current learning management system towards an intelligent virtual educational system, seeking greater benefit by exploiting the data generated by students in their day-to-day activities. Therefore, the design of these intelligent systems must be performed from a new perspective, which will take advantage of the new analytical functions provided by technologies such as artificial intelligence, big data, educational data mining techniques, and web analytics. This paper focuses on primary education in developing countries, showing the design of an intelligent virtual educational system to improve the efficiency of primary education through recommendations based on reliable data. The intelligent system is formed of four subsystems: data warehousing, analytical data processing, monitoring process and recommender system for educational agents. To illustrate this, the paper contains two dashboards that analyze, respectively, the digital resources usage time and an aggregate profile of teachers’ digital skills, in order to infer new activities that improve efficiency. These intelligent virtual educational systems focus the teaching–learning process on new forms of interaction on an educational future oriented to personalized teaching for the students, and new evaluation and teaching processes for each professor.

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Métricas de similaridad y evaluación para sistemas de recomendación de filtrado colaborativo

Cited by 4 publications

References 0 publications

Una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos tecnológicos

Una revisión de métodos, técnicas y algoritmos para sistemas de recomendación de productos tecnológicos

Ecosystem Services Assessment for Their Integration in the Analysis of Landslide Risk

Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries

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