A carregar...
Publicação
Personalization of product rankings in e-commerce
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 2.9 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
Consumers face a large number of choices while shopping online. Studies have
shown, that they are already expecting to be targeted with content addressing
their personal needs. In a web shop, products are presented as lists based on a
selected category or as results of a product search. To support the users in their
decision making, they can be provided with a personalized product ranking fitted
to their current interests.
In this piece of work, three levels of personalized product rankings are proposed:
explicit personalization, cluster-based personalization and individualization. To
estimate the potential effect of the personalization and its required effort, two
prototypes for the second and third level are developed and evaluated. The
prototypes are based on a previously existing non-personalized ranking, which
ranks the products in descending order according to a sales prediction. The
cluster-based prototype enhances this product ranking by determining customer
clusters beforehand using both situative and behavioural data. The individualized
product rankings rely on the combination of the ranking with a recommendation
system realized as a matrix factorization. In doing so, the concept of learning to
rank is considered.
By evaluating the cluster-based and individualized prototype on a sampled data
set in comparison to the non-personalized ranking, it is shown that the created
personalized rankings are in fact closer to the users’ needs. Furthermore, a subjective
evaluation confirms that the cluster-based rankings can reflect the users’
interests in a better way.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
Palavras-chave
Personalization Ranking Machine Learning Learning to Rank Clustering Recommendation system Matrix Factorization E-commerce