AToMRS: A Tool to Monitor Recommender Systems

André Costa, Tiago Cunha, Carlos Soares

Abstract

Recommender systems arose in response to the excess of available online information. These systems assign, to a given individual, suggestions of items that may be relevant. These system’s monitoring and evaluation are fundamental to the proper functioning of many business related services. It is the goal of this paper to create a tool capable of collecting, aggregating and supervising the results obtained from the recommendation systems’ evaluation. To achieve this goal, a multi-granularity approach is developed and implemented in order to organize the different levels of the problem. This tool also aims to tackle the lack of mechanisms to enable visually assessment of the performance of a recommender systems’ algorithm. A functional prototype of the application is presented, with the purpose of validating the solution’s concept.

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Paper Citation


in Harvard Style

Costa A., Cunha T. and Soares C. (2016). AToMRS: A Tool to Monitor Recommender Systems . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 133-140. DOI: 10.5220/0005992801330140


in Bibtex Style

@conference{kdir16,
author={André Costa and Tiago Cunha and Carlos Soares},
title={AToMRS: A Tool to Monitor Recommender Systems},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={133-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005992801330140},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - AToMRS: A Tool to Monitor Recommender Systems
SN - 978-989-758-203-5
AU - Costa A.
AU - Cunha T.
AU - Soares C.
PY - 2016
SP - 133
EP - 140
DO - 10.5220/0005992801330140