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title

Recommendation Systems based on Association Rule Mining for a Target Object by Evolutionary Algorithms

Credit to Download: 1 | Page Numbers 8 | Abstract Views: 174
Year: 2017
COI code: ICELE02_456
Paper Language: English

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Authors Recommendation Systems based on Association Rule Mining for a Target Object by Evolutionary Algorithms

  Hossein Hatami Varzaneh - Department of Computer Engineering, Faculty of Computer & Electrical Engineering, Kashan Branch, Islamic Azad University,Kashan, Isfahan, Iran
  Behzad Soleimani Neysiani - Department of Computer Engineering, Faculty of Computer & Electrical Engineering, University of Kashan, Kashan, Isfahan, Iran
  Hassan Ziafat - Young Researcher and Elite Club, Natanz Branch, Islamic Azad University, Natanz, Isfahan, Iran

Abstract:

Recommender systems are designed for offering products to the potential customers. Collaborative Filtering is known as a common way in Recommender systems which offers recommendations made by similar users in the case of entering time and previous transactions. Low accuracy of suggestions due to a database is one of the main concerns about collaborative filtering recommender systems. In this field, numerous researches have been done to use associative rules for recommendation systems to improve accuracy but runtime of rule-based recommendation systems is high and can not be used in real world. So, many researchers suggest using evolutionary algorithms for finding relative best rules at runtime very fast. The present study investigated the works done for producing associative rules with higher speed and quality. In the first step Apriori-based algorithm will be introduced which is used for recommendation systems and then Particle Swarm Optimization algorithm will be described and the issues of these 2 work will be discussed. Studying this research could help to know the issues in this research field and produce suggestions which have higher speed and quality

Keywords:

Recommander Systems; Collaborative Filtering; Association Rule Mining; Multi-Objective Evolutionary Algorithms; Particle Swarm Optimization; Genetic

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COI code: ICELE02_456

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Hatami Varzaneh, Hossein; Behzad Soleimani Neysiani & Hassan Ziafat, 2017, Recommendation Systems based on Association Rule Mining for a Target Object by Evolutionary Algorithms, 2nd International Conference on Electrical Engineering, تهران, دانشگاه علامه مجلسي, https://www.civilica.com/Paper-ICELE02-ICELE02_456.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Hatami Varzaneh, Hossein; Behzad Soleimani Neysiani & Hassan Ziafat, 2017)
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The University/Research Center Information:
Type: Azad University
Paper No.: 1374
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