Long Term Goal Oriented Recommender Systems

Amir Hossein Nabizadeh, Alípio Mário Jorge, José Paulo Leal


The main goal of recommender systems is to assist users in finding items of their interest in very large collections. The use of good automatic recommendation promotes customer loyalty and user satisfaction because it helps users to attain their goals. Current methods focus on the immediate value of recommendations and are evaluated as such. This is insufficient for long term goals, either defined by users or by platform managers. This is of interest in recommending learning resources to learn a target concept, and also when a company is organizing a campaign to lead users to buy certain products or moving to a different customer segment. Therefore, we believe that it would be useful to develop recommendation algorithms that promote the goals of users and platform managers (e.g. e-shop manager, e-learning tutor, ministry of culture promotor). Accordingly, we must define appropriate evaluation methodologies and demonstrate the concept on practical cases.


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Paper Citation

in Harvard Style

Hossein Nabizadeh A., Mário Jorge A. and Paulo Leal J. (2015). Long Term Goal Oriented Recommender Systems . In Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-106-9, pages 552-557. DOI: 10.5220/0005493505520557

in Bibtex Style

author={Amir Hossein Nabizadeh and Alípio Mário Jorge and José Paulo Leal},
title={Long Term Goal Oriented Recommender Systems},
booktitle={Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},

in EndNote Style

JO - Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Long Term Goal Oriented Recommender Systems
SN - 978-989-758-106-9
AU - Hossein Nabizadeh A.
AU - Mário Jorge A.
AU - Paulo Leal J.
PY - 2015
SP - 552
EP - 557
DO - 10.5220/0005493505520557