What is it about?

Allied is a framework for evaluating and deploying algorithms for a ​recommendation based on linked data.

Featured Image

Why is it important?

This paper describes how Linked Data based recommendation algorithms were re-implemented in order to measure their accuracy and performance in different application domains and without being bound to a unique dataset. Moreover, application developers can use this framework as the main component for recommendation in a given architecture. Additionally, This paper describes a new recommendation algorithm that adapts its behavior dynamically according to the characteristics of the dataset on which it is applied.

Perspectives

I hope this paper helps researchers to​ create, implement and test various combinations of recommendation algorithms to create novel and accurate recommender systems.

PhD Cristhian Figueroa
Politecnico di Torino

Read the Original

This page is a summary of: Allied, International Journal on Semantic Web and Information Systems, October 2017, IGI Global,
DOI: 10.4018/ijswis.2017100107.
You can read the full text:

Read

Contributors

The following have contributed to this page