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Recommendation research trends: review, approaches and open issues

Recommendation research trends: review, approaches and open issues Recommendation systems have been well established to reduce the problem of information overload and have become one of the most valuable tools applicable to different domains like computer science, mathematics, psychology, etc. The initial interest to write this survey is composing a concise research paper on the key motivation behind the various existing recommender systems and their techniques used in various domains. In this paper, prioritisation of recommendation keywords is presented in form of weighted keyword network along with keywords associations according to their usage in reference section literature. Consequently, this paper provides comprehensive details of various public datasets, their corresponding techniques, comparative analysis of existing recommendation approaches based on faced challenges and performance measures are examined. This study will help the researchers and academicians in quickly understanding the existing work and in planning future recommendation studies for designing a unified and coherent recommender system. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Web Engineering and Technology Inderscience Publishers

Recommendation research trends: review, approaches and open issues

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1476-1289
eISSN
1741-9212
DOI
10.1504/IJWET.2018.092831
Publisher site
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Abstract

Recommendation systems have been well established to reduce the problem of information overload and have become one of the most valuable tools applicable to different domains like computer science, mathematics, psychology, etc. The initial interest to write this survey is composing a concise research paper on the key motivation behind the various existing recommender systems and their techniques used in various domains. In this paper, prioritisation of recommendation keywords is presented in form of weighted keyword network along with keywords associations according to their usage in reference section literature. Consequently, this paper provides comprehensive details of various public datasets, their corresponding techniques, comparative analysis of existing recommendation approaches based on faced challenges and performance measures are examined. This study will help the researchers and academicians in quickly understanding the existing work and in planning future recommendation studies for designing a unified and coherent recommender system.

Journal

International Journal of Web Engineering and Technology – Inderscience Publishers

Published: Jan 1, 2018

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