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Hudup - A framework of e-commercial recommendation algorithms

Loc Nguyen, Minh-Phung Thi Do

Project introduction is published in American Association for Science and Technology (AASCIT).
Project is accepted in European Project Space.
Published as a book chapter in Ana Fred, Jan Dietz, David Aveiro, Kecheng Liu, and Joaquim Filipe (Eds.), European Project Space on Research and Applications of Information, Communication Systems, Knowledge Technology and Health Applications (EPS Lisbon 2015), volume 1, pages 10 - 43.
Trial version download.
Git source.

Hudup Introduction

View demo YouTube.

Hudup – the recommender framework dedicated to scientists and software developers who create or deploy recommendation solutions and algorithms in e-commerce and e-learning. Hudup is composed of three modules:

  • The infrastructure to set up recommendation algorithms.
  • The evaluation system to measure recommendation algorithms according to metrics.
  • The simulation environment to execute and test recommendation algorithms before deploying them in real-time applications.