Abstract
Personalized recommendation of products is an essential
feature in any e-commerce service and is becoming
more and more important for SME as well.
The main problem for e-shops of SME is to be able
to exploit limited amount of data concerning both
user interactions and item availability. In this contribution,
we describe some approaches based on
machine learning techniques that can be exploited
even in presence of limited data. They constitute
part of a recommendation plugin that is currently
developed by INFERENDO srl, an innovative startup
which is a spin-off of the University of Piemonte
Orientale.
Lingua originale | Inglese |
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Stato di pubblicazione | Pubblicato - 1 gen 2022 |
Keywords
- Recommender Systems
- SME