Exploiting Past Users’ Interests and Predictions in an Active Learning Method for Dealing with Cold Start in Recommender Systems
Journal Title: Informatics - Year 2018, Vol 5, Issue 3
Abstract
This paper focuses on the new users cold-start issue in the context of recommender systems. New users who do not receive pertinent recommendations may abandon the system. In order to cope with this issue, we use active learning techniques. These methods engage the new users to interact with the system by presenting them with a questionnaire that aims to understand their preferences to the related items. In this paper, we propose an active learning technique that exploits past users’ interests and past users’ predictions in order to identify the best questions to ask. Our technique achieves a better performance in terms of precision (RMSE), which leads to learn the users’ preferences in less questions. The experimentations were carried out in a small and public dataset to prove the applicability for handling cold start issues.
Authors and Affiliations
Manuel Pozo, Raja Chiky, Farid Meziane and Elisabeth Métais
Keywords
Related Articles
- EP ID EP44148
- DOI https://doi.org/10.3390/informatics5030035
- Views 277
- Downloads 0
Building Realistic Mobility Models for Mobile Ad Hoc Networks
A mobile ad hoc network (MANET) is a self-configuring wireless network in which each node could act as a router, as well as a data source or sink. Its application areas include battlefields and vehicular and disaster a...
Requirements and Pitfalls in AAL Projects. Guide to Self-Criticism for Developers from Experience
Since 2012, several national and international projects on ambient assisted living (AAL) active and healthy ageing gave insight into the different steps of development processes where the requirements of the target gro...
An Adaptable System to Support Provenance Management for the Public Policy-Making Process in Smart Cities
Government policies aim to address public issues and problems and therefore play a pivotal role in people’s lives. The creation of public policies, however, is complex given the perspective of large and diverse stakeho...
Improving the Classification Efficiency of an ANN Utilizing a New Training Methodology
In this work, a new approach for training artificial neural networks is presented which utilises techniques for solving the constraint optimisation problem. More specifically, this study converts the training of a neur...
Conversion of Legal Text to a Logical Rules Set from Medical Law Using the Medical Relational Model and the World Rule Model for a Medical Decision Support System
Automated formalization of legal text is a time- and effort-consuming task, but human-based validation consumes even more of both. The exchange of healthcare data in compliance with the medical privacy law requires exp...