Managing Natural Noise in Recommender Systems

  • Luis Martínez
  • Jorge Castro
  • Raciel Yera
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10071)


E-commerce customers demand quick and easy access to suitable products in large purchase spaces. To support and facilitate this purchasing process to users, recommender systems (RSs) help them to find out the information that best fits their preferences and needs in an overloaded search space. These systems require the elicitation of customers’ preferences. However, this elicitation process is not always precise either correct because of external factors such as human errors, uncertainty, human beings inherent inconsistency and so on. Such a problem in RSs is known as natural noise (NN) and can negatively bias recommendations, which leads to poor user’s experience. Different proposals have been presented to deal with natural noise in RSs. Several of them require additional interaction with customers. Others just remove noisy information. Recently, new NN approaches dealing with the ratings stored in the user/item rating matrix have raised to deal with NN in a better and simpler way. This contribution is devoted to provide a brief review of the latter approaches revising crisp and fuzzy approaches for dealing with NN in RSs. Eventually it points out as a future research the management of NN in other recommendation scenarios as group RSs.


Recommender systems Natural noise Fuzzy logic Computing with words Group recommender systems 



This research work was partially supported by the Research Project TIN2015-66524-P, and the Spanish Ministry of Education, Culture and Sport FPU fellowship (FPU13/01151).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of JaénJaénSpain
  2. 2.Department of Computer Science and A.I.University of GranadaGranadaSpain
  3. 3.Centre for Quantum Computing and Intelligent SystemsUniversity of Technology SydneyUltimoAustralia
  4. 4.University of Ciego de ÁvilaCiego de ÁvilaCuba

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