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Article

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Title

Assessment Methods for Evaluation of Recommender Systems: A Survey

Authors

Year of publication

2021

Published in

Foundations of Computing and Decision Sciences

Journal year: 2021 | Journal volume: vol. 46 | Journal number: no. 4

Article type

scientific article

Publication language

english

Keywords
EN
  • Recommender System
  • Information Filtering System
  • Assessment Methods
Abstract

EN The recommender system (RS) filters out important information from a large pool of dynamically generated information to set some important decisions in terms of some recommendations according to the user’s past behavior, preferences, and interests. A recommender system is the subclass of information filtering systems that can anticipate the needs of the user before the needs are recognized by the user in the near future. But an evaluation of the recommender system is an important factor as it involves the trust of the user in the system. Various incompatible assess- ment methods are used for the evaluation of recommender systems, but the proper evaluation of a recommender system needs a particular objective set by the recom- mender system. This paper surveys and organizes the concepts and definitions of various metrics to assess recommender systems. Also, this survey tries to find out the relationship between the assessment methods and their categorization by type.

Date of online publication

17.12.2021

Pages (from - to)

393 - 421

DOI

10.2478/fcds-2021-0023

URL

https://www.sciendo.com/pl/article/10.2478/fcds-2021-0023

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

40

Ministry points / journal in years 2017-2021

40

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