2 research outputs found
Bird diversity and land use on the slopes of Mt Kilimanjaro and the adjacent plains, Tanzania
No full textThis study of bird distribution in the main land-use categories of the slopes of Mt Kilimanjaro, Tanzania, aims at understanding potential impacts of the land-use changes on birds. A land-use map of the study area was derived from a Landsat image, and land-use change information came from an earlier study by the author. Bird data were collected by observations along timed, standardized walks. Shannon (1948) indices of bird diversity for highlands, bushland and lowlands were 3.29, 2.99, and 2.62. The highland category was divided into two subcategories, homegarden and highland garden, as bird populations of the two were distinct. Highland garden had a higher diversity (3.15) than homegarden (3.07). The lower species diversity and number of individuals in homegardens was probably due to lower niche diversity and more human disturbance. Lowland fields had low diversity indices as they are dominated by large flocks of birds. The equitability indices for highlands, bushlands and lowlands were 0.82, 0.80 and 0.65, respectively. Each land-use type had many species that were not seen in the others. As bushland is disappearing, the species currently threatened are the 15 bushland species that are not found in other land-use types. Growing population pressure leading to deagrarianization of the homegarden area is likely to affect homegarden bird populations, though it is not clear whether the very high human population density will prevent it from supporting a highland garden type of a bird population.Key words: similarity, biodiversity, land-use change
Development and implementation of recommendation systems
No full textEste proyecto se desarrolló en colaboración con Compensar, una de las principales entidades de bienestar y caja de compensación en Colombia, con el objetivo de optimizar la selección de productos para eventos mediante un sistema de recomendación basado en contenido. Para ello, se implementa-ron técnicas avanzadas de procesamiento de lenguaje natural (PLN), utilizando el modelo TF-IDF (Term Frequency-Inverse Document Frequency) para extraer y analizar atributos clave de los pro-ductos, tales como su categoría, nombre y el evento sugerido. A partir del análisis de palabras clave y similitudes textuales, el sistema identifica los productos más relevantes para cada evento.
Adicionalmente, se incorporó un modelo de Naive Bayes Multinomial para la categorización de productos, lo que permitió una organización más eficiente y precisa de los mismos. Este modelo, entrenado con datos previamente etiquetados, mejora la alineación entre los productos y los distintos
tipos de eventos, facilitando la toma de decisiones en la planificación y logística.
El objetivo principal del sistema es proporcionar recomendaciones personalizadas y precisas, mejo-rando la experiencia del usuario y optimizando la gestión de eventos en Compensar. La validación del sistema se llevó a cabo mediante métricas clave, como la exactitud en la clasificación y la retro-alimentación de los usuarios, lo que garantiza su eficacia y escalabilidad en distintos escenarios de datos.This project was developed in collaboration with Compensar, one of the leading welfare and compensation fund entities in Colombia, with the aim of optimizing product selection for events through a content-based recommendation system. To achieve this, advanced natural language processing (NLP) techniques were implemented, utilizing the TF-IDF (Term Frequency-Inverse Document Frequency) model to extract and analyze key product attributes, such as category, name, and suggested event. Based on keyword analysis and textual similarities, the system identifies the most relevant products for each event.
Additionally, a Multinomial Naive Bayes model was incorporated for product categorization, enabling a more efficient and precise organization of items. This model, trained with previously labeled data, improves the alignment between products and different event types, facilitating decision-making in planning and logistics.
The primary objective of the system is to provide personalized and accurate recommendations, enhancing the user experience and optimizing event management at Compensar. The system was validated using key metrics, such as classification accuracy and user feedback, ensuring its effectiveness and scalability across different data scenarios
