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Dharahas Tallapally, John Wang, Katerina Potika and Magdalini Eirinaki
Recommender systems have revolutionized the way users discover and engage with content. Moving beyond the collaborative filtering approach, most modern recommender systems leverage additional sources of information, such as context and social network dat...
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Kashif Zia, Muhammad Shafi and Umar Farooq
The latest manifestation of ?all connected world" is the Internet of Things (IoT), and Internet of Vehicles (IoV) is one of the key examples of IoT these days. In Social IoV (SIoV), each vehicle is treated as a social object where it establishes and mana...
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Jiping Liu, Zhiran Zhang, Chunyang Liu, Agen Qiu and Fuhao Zhang
With the rapid development of location-based social networks (LBSNs), because human behaviors exhibit specific distribution patterns, personalized geo-social recommendation has played a significant role for LBSNs. In addition to user preference and socia...
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Renata Lopes Rosa,Eduardo Lucio Lasmar Junior,Demóstenes Zegarra Rodríguez
Pág. 359 - 366
In recent years, the shared mobility service hasincreased in many countries across the world because its low cost and several shared-use mobility applications on mobile devices. Commonly, if a ride is shared between people with similar preferences, users...
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Yan Zhou, Kaixuan Zhou and Shuaixian Chen
The rapid development of big data technology and mobile intelligent devices has led to the development of location-based social networks (LBSNs). To understand users? behavioral patterns and improve the accuracy of location-based services, point-of-inter...
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Loris Belcastro, Domenico Carbone, Cristian Cosentino, Fabrizio Marozzo and Paolo Trunfio
Since the advent of Bitcoin, the cryptocurrency landscape has seen the emergence of several virtual currencies that have quickly established their presence in the global market. The dynamics of this market, influenced by a multitude of factors that are d...
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Jibouni Ayoub, Dounia Lotfi and Ahmed Hammouch
The analysis of social networks has attracted a lot of attention during the last two decades. These networks are dynamic: new links appear and disappear. Link prediction is the problem of inferring links that will appear in the future from the actual sta...
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Abrar A. Almuhanna, Wael M. S. Yafooz and Abdullah Alsaeedi
In this era of digital transformation, when the amount of scholarly literature is rapidly growing, hundreds of papers are published online daily with regard to different fields, especially in relation to academic subjects. Therefore, it difficult to find...
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Ruijing Li, Jianzhong Guo, Chun Liu, Zheng Li and Shaoqing Zhang
With the popularity of location-based social networks such as Weibo and Twitter, there are many records of points of interest (POIs) showing when and where people have visited certain locations. From these records, next POI recommendation suggests the ne...
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Xueying Wang, Yanheng Liu, Xu Zhou, Zhaoqi Leng and Xican Wang
The next point-of-interest (POI) recommendation is one of the most essential applications in location-based social networks (LBSNs). Its main goal is to research the sequential patterns of user check-in activities and then predict a user?s next destinati...
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Yi-Chung Chen, Hsi-Ho Huang, Sheng-Min Chiu and Chiang Lee
Joint promotion is a valuable business strategy that enables companies to attract more customers at lower operational cost. However, finding a suitable partner can be extremely difficult. Conventionally, one of the most common approaches is to conduct su...
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Franco Bagnoli, Guido de Bonfioli Cavalcabo?, Banedetto Casu and Andrea Guazzini
We investigate the problem of the formation of communities of users that selectively exchange messages among them in a simulated environment. This closed community can be seen as the prototype of the bubble effect, i.e., the isolation of individuals from...
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Sadaf Safavi and Mehrdad Jalali
In location-based social networks (LBSNs), exploit several key features of points-of-interest (POIs) and users on precise POI recommendation be significant. In this work, a novel POI recommendation pipeline based on the convolutional neural network named...
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Ali M. Ahmed Al Sabaawi,Hacer Karacan,Yusuf Erkan Yenice
Pág. pp. 70 - 87
Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems by alleviating RSs drawbacks. The most common limitations are sparsity and the cold-start pr...
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Robert Albert Klopotek
This paper describes the modeling of social networks subject to a recommendation. The Cold Start User-Item Model (CSUIM) of a bipartite graph is considered, which simulates bipartite graph growth based on several parameters. An algorithm is proposed to c...
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Wenchao Li, Xin Liu, Chenggang Yan, Guiguang Ding, Yaoqi Sun and Jiyong Zhang
The rapidly growing location-based social network (LBSN) has become a promising platform for studying users? mobility patterns. Many online applications can be built based on such studies, among which, recommending locations is of particular interest. Pr...
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Heba M. Wagih, Hoda M. O. Mokhtar and Samy S. Ghoniemy
Recently, social networks have shown huge potential in terms of collaborative web services and the study of peer influence as a result of the massive amount of data, datasets, and interrelations generated. These interrelations cannot guarantee the succes...
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Mingxin Gan and Ling Gao
Point-of-interest (POI) recommendations in location-based social networks (LBSNs) allow online users to discover various POIs for social activities occurring in the near future close to their current locations. Research has verified that people?s prefere...
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Jun Long, Yulou Wang, Xinpan Yuan, Ting Li and Qunfeng Liu
This paper proposed a recommendation model called RM-SA, which is based on multi-emotional analysis in networks. In the RM-MES scheme, the recommendation values of goods are primarily derived from the probabilities calculated by a similar existing recomm...
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Yelyzaveta Meleshko
Pág. 80 - 85
The subject matter of the article is the process of modeling social networks. The goal is to develop a computer model of a social network with a recommendation system. The tasks to be solved are to research the methods of generating social networks, to r...
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