2019
DOI: 10.25046/aj040454
|View full text |Cite
|
Sign up to set email alerts
|

A Fuzzy-Based Approach and Adaptive Genetic Algorithm in Multi-Criteria Recommender Systems

Abstract: Recommender Systems (RSs) are termed as web-based applications that make use of filtering methods and several machine learning algorithms to suggest relevant user objects. It can be said that some techniques are usually adopted or trained to develop these systems that generate lists of suitable recommendations. Conventionally, RS uses a single rating approach to preference user recommendation over an item. Recently, multi-criteria technique has been identified as a new approach of recommending user items based… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
2
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
3

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(3 citation statements)
references
References 16 publications
0
2
0
Order By: Relevance
“…The aggregation function was applied based on an adaptive GA and was developed to improve the MCRS extrapolation capabilities. Similarly, Hamada et al [ 29 ] proposed adaptive GA and fuzzy logic-based recommendation models to integrate the multi-criteria ratings into the traditional RS. Results inferred that their developed models gave better results in comparison to traditional CF-based RS.…”
Section: Background and Related Workmentioning
confidence: 99%
“…The aggregation function was applied based on an adaptive GA and was developed to improve the MCRS extrapolation capabilities. Similarly, Hamada et al [ 29 ] proposed adaptive GA and fuzzy logic-based recommendation models to integrate the multi-criteria ratings into the traditional RS. Results inferred that their developed models gave better results in comparison to traditional CF-based RS.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Any genetic algorithm [17] is built around a solution represented by its chromosomes [18] which are then passed on to their offspring [19]. In GAs [20], it is common to represent each solution with a binary string [21]. Each bit indicates whether the solution has a particular characteristic or not and uses numbers to denote the strength of a function in a solution.…”
Section: Initial Populationmentioning
confidence: 99%
“…However, other methods work by assuming a solid relationship between criteria ratings and the overall rating as used in [20,[29][30][31][32][33]. For instance, in Table 1, one can observe that the overall rating r 0 has a well-defined relationship with the rating of their corresponding criteria r 1 , r 2 , r 3 , and r 4 .…”
Section: Multi-criteria Rsmentioning
confidence: 99%