A carregar...
Publicação
Developing a dynamic recommender system for the aftermarket car industry. developing and designing of dashboard for visualizing data in a traceable way - the tips4y use case
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 1.35 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Recommendation systems are a powerful tool for e-commerce businesses when applied properly. After extensive research on the various models used in the market, a recommendation system was successfully designed, with the purpose of helping TIPS 4Y support after-market distributors by optimizing the recommendation of auto parts. Adopting a CRIPS-DM framework, an Item-Based Collaborative Filtering was developed, with the data provided by TIPS 4Y, that performed far better than the other two baseline models. Attempts to improve the model, Dimensionality Reduction techniques were tested. A data dashboard was also designed, allowing TIPS 4Y to make management decisions on working with data.
Descrição
Palavras-chave
Data science Business analytics Recommendation system Tips4y Automotive aftermarket Dimensionality reduction Data dashboard Business analysis