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A Comparison of BAT and Firefly Algorithm in Neighborhood based Collaborative Filtering

Hartatik -, Bayu Permana Sejati, Hamdani Hamdani, Andri Syafrianto
2021 International Journal of Advanced Computer Science and Applications  
The recommender system is a knowledge-based filtering system that predicts the users' rating and preference for what they might desire.  ...  The intelligent swarm technique used to compare its accuracy to help provide recommendations is the Firefly and Bat Algorithm.  ...  Plenty of techniques can develop recommendation systems such as Content-Based Filtering, Collaborative Filtering, and Knowledge-Based Filtering.  ... 
doi:10.14569/ijacsa.2021.0120972 fatcat:o4wg4yi6xvbabijgdpbypyqytq

Comparison of Recommendation Using Social Network Analysis with Collaborative Filtering in Social Network Sites
SNS에서 사회연결망 기반 추천과 협업필터링 기반 추천의 비교

Sangun Park
2014 Journal of the Korea society of IT services  
It is expected that graph-based analysis on the semantic social network and systematic comparative analysis on the performances of social filtering and collaborative filtering are required.  ...  As the results of the analysis, we suggested the trends and implications for future research of recommendation in SNSs.  ...  Traditionally, collaborative filtering (CF) was used a lot for recommendation of products and services.  ... 
doi:10.9716/kits.2014.13.2.173 fatcat:djbo2phtxfgp7nysyucsp4lafm

Research on User Clustering Collaborative Filtering Algorithm

Lihua Tian, Liguo Han, Junhua Yue
2016 International Journal of Hybrid Information Technology  
Memory-based CF algorithms have the weakness of low real-time ability and scalability. For these issues, a SVD-based K-means clustering CF algorithm is proposed.  ...  This algorithm overcomse the data sparsity issue via SVD and keep the advantage of clustering, such as good real-time ability and scalability.  ...  Comparison of Recommended Performance of Different Clustering Numbers Sarwar et al.applied SVD technique in collaborative filtering.  ... 
doi:10.14257/ijhit.2016.9.4.01 fatcat:4dfnrwjocvet5fvu45dpmuerce

An Improved Online Book Recommender System using Collaborative Filtering Algorithm

E. Uko, B. O., P. O.
2018 International Journal of Computer Applications  
We will design and develop a recommendation model that uses object-oriented analysis and design methodology (OOADM), improved collaborative filtering algorithm and an efficient quick sort algorithm to  ...  From the results, the speed and scalability of book recommendation was improved with a performance record obtained within the range of ninety (90) to ninety-five (95) per cent using the root mean square  ...  of performance. [3] proposed RegionKNN: a scalable hybrid collaborative filtering algorithm for personalized web service recommendations.  ... 
doi:10.5120/ijca2018917193 fatcat:vw5da62mqrf7rlvmu7ucqkpyiy

Personalized Recommender by Exploiting Domain based Expert for Enhancing Collaborative Filtering Algorithm :PReC

Mrs.M Sridevi, Dr.R.Rajeswara Rao
2019 International Journal of Advanced Computer Science and Applications  
Personalized Expert based collaborative filtering (PReC) approach is proposed to identify domain specific experts and the use of experts preference enhanced the performance of collaborative filtering recommender  ...  Collaborative filtering is one of the most traditional and intensively used recommendation approaches for many commercial services.  ...  Table III gives the comparison of MAE values for all the proposed algorithms for different sizes of neighborhood.  ... 
doi:10.14569/ijacsa.2019.0100313 fatcat:j54k25smrrgwjo56agrtefwodm

Real-time recommendation algorithms for crowdsourcing systems

Mejdl Safran, Dunren Che
2017 Applied Computing and Informatics  
Traditional recommendation algorithms such as collaborative filtering no longer work satisfactorily because of the unprecedented data flow and the on-the-fly nature of the tasks in crowdsourcing systems  ...  In this article, we propose two real-time recommendation algorithms for crowdsourcing systems: (1) TOP-K-T that computes the top-k most suitable tasks for a given worker and (2) TOP-K-W that computes the  ...  Current recommendation systems are based on two main approaches, i.e., content filtering and collaborative filtering.  ... 
doi:10.1016/j.aci.2016.01.001 fatcat:gzamys5hxzecpaq23bkk2yioku

A Novel Approach for Keyword-Aware Service Recommendation System using Collaborative- Filtering Algorithm to Implement in Hadoop Framework

Mr. Vengateshwaran M., Janarthanan T.S, Senbagam S, Shanmugapriya S
2017 IJARCCE  
In this system user based collaborative filtering algorithm is used to generate recommendations. To improve the efficiency here we implement the system in Hadoop.  ...  In the existing recommendation system, the ratings of services and the service recommendation lists presented to users are the same.In the existing system the major problem is scalability and inefficiency  ...  In this system, they implement the process using the collaborative filtering algorithm. But the problem occurs in this system is the scalability problem.  ... 
doi:10.17148/ijarcce.2017.6687 fatcat:omuk7dlv35f3xcwgwp67rqrsd4

Trust inference algorithms for social networks

Maha Faisal, Asmaa Alsumait, Zainab Al-ameer
2014 Maǧallaẗ al-abḥāṯ al-handasiyyaẗ  
We compared the time complexity and the accuracy of the following four adapted algorithms and a new proposed algorithm:  ...  Such systems are designed to offer recommendations of trustworthiness when establishing connections among social network members, where the system rates members by inferring their degrees of trust.  ...  ACKNOWLEDGEMENT The authors would like to acknowledge the support of Kuwait University under research grant no. EO03/11.  ... 
doi:10.7603/s40632-014-0003-2 fatcat:qmbmhfnafvc2bpx62skw5j2dom

Recommendation System Algorithms on Location-Based Social Networks: Comparative Study

Abeer Al-Nafjan, Norah Alrashoudi, Hend Alrasheed
2022 Information  
The primary task of the implemented recommender system was to predict restaurant ratings for each user and make a recommendation based on this prediction.  ...  Location rec-14 recommendation system-based LBSN has gained considerable attention in research using techniques and methods based on users' geosocial activities.  ...  NMF is used extensively in recommendation systems for content-and collaborative filtering-based recommendations. Massimo et al.  ... 
doi:10.3390/info13040188 fatcat:sqezxozdffdhbnquj3kw5mbbx4

Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities

Zeshan Fayyaz, Mahsa Ebrahimian, Dina Nawara, Ahmed Ibrahim, Rasha Kashef
2020 Applied Sciences  
This article provides an overview of the current state of the art in recommendation systems, their types, challenges, limitations, and business adoptions.  ...  This paper provides the current landscape of recommender systems research and identifies directions in the field in various applications.  ...  [54] has proposed a framework to choose an optimal collaborative filtering algorithm.  ... 
doi:10.3390/app10217748 fatcat:vihdurtwrzcsxktolbgd6lqg7y

Personalized Music Recommendation Simulation Based on Improved Collaborative Filtering Algorithm

Hui Ning, Qian Li, Wei Wang
2020 Complexity  
Collaborative filtering technology is currently the most successful and widely used technology in the recommendation system. It has achieved rapid development in theoretical research and practice.  ...  Based on the above improvements, the improved collaborative filtering recommendation algorithm in this paper has greatly improved the prediction accuracy.  ...  value decomposition collaborative filtering and K-means based collaborative filtering, this algorithm has better prediction performance and good scalability.  ... 
doi:10.1155/2020/6643888 fatcat:cqfikrqo7nehneqztobifq5x3i

A Hybrid Web Recommendation System based on the Improved Association Rule Mining Algorithm [article]

Ujwala Wanaskar, Sheetal Vij, Debajyoti Mukhopadhyay
2013 arXiv   pre-print
In the recent research we found that the efficient technique based on asso-ciation rule mining algorithm is proposed in order to solve the problem of web page recommendation.  ...  Generally the recommendation systems are divided into two major categories such as collaborative recommendation system and content based recommendation system.  ...  Collaborative filtering Collaborative filtering became one of the most researched techniques of recommender systems since this approach was mentioned and described by Paul Resnick and Hal Varian in 1997  ... 
arXiv:1311.7204v1 fatcat:smu6oymaejhk3gwx5ounttcqve

An Improved Collaborative Filtering Recommendation Algorithm and Recommendation Strategy

Xiaofeng Li, Dong Li
2019 Mobile Information Systems  
The experimental results show that the improved collaborative filtering algorithm is superior to other two collaborative recommendation algorithms for MAE and RMSE performance.  ...  This paper has a perfect combination of social network technology and collaborative filtering technology, which can greatly increase recommendation system performance.  ...  accurate, fast, and effective high-scalable recommendation system has become the trend of research. is paper combines the social network technology with the collaborative filtering recommendation technique  ... 
doi:10.1155/2019/3560968 fatcat:f56ahm6ozfhobexp6aysgroy44

Recommendation Systems an overview, Types, Algorithms and Artificial Intelligence

Diako_Kaso
2022 Zenodo  
Recommender systems represent user preferences for the purpose of suggesting items to purchase or examine.  ...  The recommendation system is a system that learns from the user's previous actions and predicts their current preferences and generally is categorized into four Main classes; these include Collaborative  ...  Hybrid Filtering-based recommender systems For better results, some recommender systems combine different techniques of collaborative approaches and content-based approaches.  ... 
doi:10.5281/zenodo.7013632 fatcat:tvp3dvh6mve2npwmbdd74zuwtq

An Item-based Multi-Criteria Collaborative Filtering Algorithm for Personalized Recommender Systems

Qusai Shambour, Mou'ath Hourani, Salam Fraihat
2016 International Journal of Advanced Computer Science and Applications  
However, Item-based Collaborative Filtering (CF) techniques, as the most popular techniques of recommender systems, suffer from sparsity and new item limitations which result in producing inaccurate recommendations  ...  This paper proposes an Item-based Multi-Criteria Collaborative Filtering algorithm that integrates the items' semantic information and multi-criteria ratings of items to lessen known limitations of the  ...  Collaborative filtering (CF) is one of the most known techniques in recommender systems to generate personalized recommendations.  ... 
doi:10.14569/ijacsa.2016.070837 fatcat:6h2k32m7zvf6fm5vh2esxhbdqa
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