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The Role of Trust to Enhance the Recommendation System Based on Social Network

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@article{IJASEIT10883,
   author = {Muhammed E Abd Alkhalec Tharwat and Deden Witarsyah Jacob and Mohd Farhan Md Fudzee and Shahreen Kasim and Azizul Azhar Ramli and Muharman Lubis},
   title = {The Role of Trust to Enhance the Recommendation System Based on Social Network},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {10},
   number = {4},
   year = {2020},
   pages = {1387--1395},
   keywords = {recommendation system; recommender system; trust; distrust; social network.},
   abstract = {

Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is widely utilized to predict an item to the end-user based on his/her preferences primary. Recommendation systems applied in many areas mainly in commercial applications. This work aims to collect evidence of utilizing social network information between users to enhance the quality of traditional recommendation system. It provides an overview of traditional and modern approaches used by RSs such as collaborative filter (CF) approach, content-based (CB) approach, and hybrid filter approach. CF is one of the most famous traditional approaches in RSs, which is facing many limitations due to the lack of information available during a performance such as Cold start, Sparsity and Shilling attack. Additionally, this content focused on the role of incorporating a trust relationship from the social network to enhance the weaknesses of CF and achieve better quality in the recommendation process. Trust-aware Recommendation Systems (TaRSs) is a modern approach proposed to overcome the limitations of CF recommendation system in a social network. The trust relationship between users can boost and enhance CF limitations. Many researchers are focusing on trust in the recommendation system but fewer works are highlighting the role of trust in the recommendation system. In the end, limitations, and open issues of the current picture of the recommendation system come across. 

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10883},    doi = {10.18517/ijaseit.10.4.10883} }

EndNote

%A Tharwat, Muhammed E Abd Alkhalec
%A Jacob, Deden Witarsyah
%A Md Fudzee, Mohd Farhan
%A Kasim, Shahreen
%A Ramli, Azizul Azhar
%A Lubis, Muharman
%D 2020
%T The Role of Trust to Enhance the Recommendation System Based on Social Network
%B 2020
%9 recommendation system; recommender system; trust; distrust; social network.
%! The Role of Trust to Enhance the Recommendation System Based on Social Network
%K recommendation system; recommender system; trust; distrust; social network.
%X 

Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is widely utilized to predict an item to the end-user based on his/her preferences primary. Recommendation systems applied in many areas mainly in commercial applications. This work aims to collect evidence of utilizing social network information between users to enhance the quality of traditional recommendation system. It provides an overview of traditional and modern approaches used by RSs such as collaborative filter (CF) approach, content-based (CB) approach, and hybrid filter approach. CF is one of the most famous traditional approaches in RSs, which is facing many limitations due to the lack of information available during a performance such as Cold start, Sparsity and Shilling attack. Additionally, this content focused on the role of incorporating a trust relationship from the social network to enhance the weaknesses of CF and achieve better quality in the recommendation process. Trust-aware Recommendation Systems (TaRSs) is a modern approach proposed to overcome the limitations of CF recommendation system in a social network. The trust relationship between users can boost and enhance CF limitations. Many researchers are focusing on trust in the recommendation system but fewer works are highlighting the role of trust in the recommendation system. In the end, limitations, and open issues of the current picture of the recommendation system come across. 

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10883 %R doi:10.18517/ijaseit.10.4.10883 %J International Journal on Advanced Science, Engineering and Information Technology %V 10 %N 4 %@ 2088-5334

IEEE

Muhammed E Abd Alkhalec Tharwat,Deden Witarsyah Jacob,Mohd Farhan Md Fudzee,Shahreen Kasim,Azizul Azhar Ramli and Muharman Lubis,"The Role of Trust to Enhance the Recommendation System Based on Social Network," International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 4, pp. 1387-1395, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.4.10883.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Tharwat, Muhammed E Abd Alkhalec
AU  - Jacob, Deden Witarsyah
AU  - Md Fudzee, Mohd Farhan
AU  - Kasim, Shahreen
AU  - Ramli, Azizul Azhar
AU  - Lubis, Muharman
PY  - 2020
TI  - The Role of Trust to Enhance the Recommendation System Based on Social Network
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 4
Y2  - 2020
SP  - 1387
EP  - 1395
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - recommendation system; recommender system; trust; distrust; social network.
N2  - 

Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is widely utilized to predict an item to the end-user based on his/her preferences primary. Recommendation systems applied in many areas mainly in commercial applications. This work aims to collect evidence of utilizing social network information between users to enhance the quality of traditional recommendation system. It provides an overview of traditional and modern approaches used by RSs such as collaborative filter (CF) approach, content-based (CB) approach, and hybrid filter approach. CF is one of the most famous traditional approaches in RSs, which is facing many limitations due to the lack of information available during a performance such as Cold start, Sparsity and Shilling attack. Additionally, this content focused on the role of incorporating a trust relationship from the social network to enhance the weaknesses of CF and achieve better quality in the recommendation process. Trust-aware Recommendation Systems (TaRSs) is a modern approach proposed to overcome the limitations of CF recommendation system in a social network. The trust relationship between users can boost and enhance CF limitations. Many researchers are focusing on trust in the recommendation system but fewer works are highlighting the role of trust in the recommendation system. In the end, limitations, and open issues of the current picture of the recommendation system come across. 

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10883 DO - 10.18517/ijaseit.10.4.10883

RefWorks

RT Journal Article
ID 10883
A1 Tharwat, Muhammed E Abd Alkhalec
A1 Jacob, Deden Witarsyah
A1 Md Fudzee, Mohd Farhan
A1 Kasim, Shahreen
A1 Ramli, Azizul Azhar
A1 Lubis, Muharman
T1 The Role of Trust to Enhance the Recommendation System Based on Social Network
JF International Journal on Advanced Science, Engineering and Information Technology
VO 10
IS 4
YR 2020
SP 1387
OP 1395
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 recommendation system; recommender system; trust; distrust; social network.
AB 

Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is widely utilized to predict an item to the end-user based on his/her preferences primary. Recommendation systems applied in many areas mainly in commercial applications. This work aims to collect evidence of utilizing social network information between users to enhance the quality of traditional recommendation system. It provides an overview of traditional and modern approaches used by RSs such as collaborative filter (CF) approach, content-based (CB) approach, and hybrid filter approach. CF is one of the most famous traditional approaches in RSs, which is facing many limitations due to the lack of information available during a performance such as Cold start, Sparsity and Shilling attack. Additionally, this content focused on the role of incorporating a trust relationship from the social network to enhance the weaknesses of CF and achieve better quality in the recommendation process. Trust-aware Recommendation Systems (TaRSs) is a modern approach proposed to overcome the limitations of CF recommendation system in a social network. The trust relationship between users can boost and enhance CF limitations. Many researchers are focusing on trust in the recommendation system but fewer works are highlighting the role of trust in the recommendation system. In the end, limitations, and open issues of the current picture of the recommendation system come across. 

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10883 DO - 10.18517/ijaseit.10.4.10883