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A Motivation-Aware Approach for Point of Interest Recommendations

Khadija Vakeel, Sanjog Ray
2016 ACM Conference on Recommender Systems  
Most existing context aware recommender systems primarily use a combination of ratings data, content data like features or attributes of the product or service, context data like location or time and social  ...  In this paper, we propose a novel approach for refining the recommendations made by locationaware recommender systems based on user motivations for checking in at locations in location based social networks  ...  from location based social networks.  ... 
dblp:conf/recsys/VakeelR16 fatcat:6rgk4uwusnfmtfzr5myy4bgawi

Analysis and Applications of Location-Aware Big Complex Network Data

Jianxin Li, Ke Deng, Xin Huang, Jiajie Xu
2019 Complexity  
Conflicts of Interest The authors declare that they have no conflicts of interest. Tang et al. improved the community detection method for high-quality point-of-interest recommendation.  ...  Challenges include real-time event detection in a city, congestion discovery in a traffic network, location prediction of social users, social users' behavior recognition in physical world, and unified  ... 
doi:10.1155/2019/3410262 fatcat:klkq3sed5fby3cfycdbth57rba

Enhancing Location-Based Social Media Network Services with Semantic Technologies: A Review

Olayinka Adeleye, Opeyemi Ajibola, Precious Odiase
2017 FUOYE Journal of Engineering and Technology  
Location-based social media application can now recommend point of interest to users based on geographical information and user's profile gatheredon social media networks.  ...  However, unprecedented amount of noise and unstructured data exist on these networks, making knowledge representation, point of interest recommendation and precision of search engine results cumbersome  ...  Users now have access to global and valuable services based on their location, context- awareness and social interest.  ... 
doi:10.46792/fuoyejet.v2i1.50 fatcat:3w7rfefp3ndrvnfbnxsrnb37pi

A Context-Awareness Personalized Tourist Attraction Recommendation Algorithm

Zhijun Zhang, Huali Pan, Gongwen Xu, Yongkang Wang, Pengfei Zhang
2016 Cybernetics and Information Technologies  
With the rapid development of social networks, location based social network gradually rises.  ...  This algorithm fully exploits social relations and trust friendship between users, and by means of the geographic information between user and attraction location, recommends users most interesting attractions  ...  User-based collaborative filtering algorithm In the location-based social network, users and location are linked by check-in.  ... 
doi:10.1515/cait-2016-0084 fatcat:vjvghekjqvdklnky5bmpghl75a


Mohamed Sarwat, Jie Bao, Ahmed Eldawy, Justin J. Levandoski, Amr Magdy, Mohamed F. Mokbel
2012 Proceedings of the 2012 international conference on Management of Data - SIGMOD '12  
Sindbad supports three new services beyond traditional social networking services, namely, location-aware news feed, location-aware recommender, and location-aware ranking.  ...  This demo presents Sindbad; a location-based social networking system.  ...  The main idea of the location-aware news feed module (Ge-oFeed) is to abstract the location-aware news feed problem into one that evaluates a set of location-based point queries against each friend in  ... 
doi:10.1145/2213836.2213923 dblp:conf/sigmod/SarwatBELMM12 fatcat:5xdntwexk5gwdhc4nu5cu75ogy

User modeling for point-of-interest recommendations in location-based social networks: the state-of-the-art [article]

Shudong Liu
2017 arXiv   pre-print
Location-based social networks(LBSNs)allow users to check-in at a physical location and share daily tips on points-of-interest (POIs) with their friends anytime and anywhere.  ...  The rapid growth of location-based services(LBSs)has greatly enriched people's urban lives and attracted millions of users in recent years.  ...  Acknowledgements This work is supported by National Scien ce Foundation of China (NO. 61602518) and Open Foundation of Hubei Key Laboratory of Intelligent Geo-Information Processing (No.K  ... 
arXiv:1712.06768v1 fatcat:nzmsjj6kjzby7ldi3czf6zlkye

Mining social networks for local search and location-based recommender systems

Fabio Gasparetti, Damianos Gavalas, Sergio Ilarri, Francesco Ricci, Zhiwen Yu
2019 Personal and Ubiquitous Computing  
Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.  ...  We would like to thank especially the authors of the accepted papers for their effort in revising and improving their work (occasionally, several times) in response to reviewers' comments.  ...  Many thanks also go to the PUC Editor-in-Chief Prof. Peter Thomas for his trust, guidance and support.  ... 
doi:10.1007/s00779-019-01241-0 fatcat:4uhdujarjbe47maeang2j6aa5e

The anatomy of Sindbad

Mohamed Sarwat, Jie Bao, Ahmed Eldawy, Justin J. Levandoski, Amr Magdy, Mohamed F. Mokbel
2012 Proceedings of the 5th International Workshop on Location-Based Social Networks - LBSN '12  
Sindbad supports three new services beyond traditional social networking services, namely, location-aware news feed, location-aware recommender, and location-aware ranking.  ...  This paper features Sindbad; a location-based social networking system.  ...  INTRODUCTION In this paper we feature Sindbad [10] : a location-based social networking system.  ... 
doi:10.1145/2442796.2442798 dblp:conf/gis/Sarwat0EL0M12 fatcat:wrapaascgva63beslyqjmfc4ri

Context-aware intelligent recommendation system for tourism

Kevin Meehan, Tom Lunney, Kevin Curran, Aiden McCaughey
2013 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)  
However, using additional context data such as weather, time, social media sentiment and user preferences can provide a more accurate model of the user's current context.  ...  In recent years there has also been a renewed requirement to use more types of context and reduce the current over-reliance on location as a context.  ...  A CONTEXT AWARE TOURIST APP The five main types of contextual data that will be used in this research are location, time, weather, social media sentiment and personalisation.  ... 
doi:10.1109/percomw.2013.6529508 dblp:conf/percom/MeehanLCM13 fatcat:4jrapyfewfe37llfjbgh6z6rcu

Recommendations in location-based social networks: a survey

Jie Bao, Yu Zheng, David Wilkie, Mohamed Mokbel
2015 Geoinformatica  
We refer to these social networks as location-based social networks (LBSNs).  ...  This article presents a panorama of the recommender systems in location-based social networks with a balanced depth, facilitating research into this important research theme.  ...  The Rate of Growth Location-based social networks evolve at a faster pace than traditional social networks in both social structure and properties of nodes and links.  ... 
doi:10.1007/s10707-014-0220-8 fatcat:3ivmtrnvkfhshl72gd33h4aola

Building Context-Rich Mobile Cloud Services For Mobile Cloud Applications

Aleksandar Karadimce
2015 Zenodo  
Therefore, mobile applications will have to become more personalized, context aware, and able to recognize not only the location of the user, but also their cognitive preferences.  ...  The essence of the proposed model will consider the different aspects and influencing factors that are part of the Quality of Experience (QoE) process and metrics.  ...  Further research is needed to expand the number of context-rich mCloud services that will be relevant for mCloud social networking applications.  ... 
doi:10.5281/zenodo.33143 fatcat:ah2mckho2zgnncjqz56xjjmvyy

Personalized Recommendation System Based on WSN

Zhijun Zhang, Gongwen Xu, Pengfei Zhang, Yongkang Wang
2016 International Journal of Online Engineering (iJOE)  
technology in the personalized recommendation system, a new user modeling method based on wireless sensor network and ontology technology is introduced in this paper.  ...  In order to retrieve the tourist attractions conforming to the users' needs from a large amount of the tourist information, a personalized recommendation model based on the ontology technology and travel  ...  [2] explore user preference, social influence and geographical influence for POI (Point of Interest) recommendations.  ... 
doi:10.3991/ijoe.v12i10.6207 fatcat:jfl6hgtd6vblfb5onipl5sosbu

Research on Point of Interest Recommendation Algorithm Based on Spatial Clustering

Liguo Zheng, Dept. of Computer and Information Engineering School, Harbin Normal University, China
2020 International Journal of Multimedia and Ubiquitous Engineering  
In order to solve the problem of recommendation of points of interest, this paper proposes an algorithm of recommendation of points of interest based on user check-in space clustering.  ...  Then the recommendation scores of candidate recommendation points were calculated according to the user preference model, social relation model and geographical correlation model.  ...  Zheng et al., in literature [14] , proposed a recommendation service for location-aware points of interest located in urban shopping centers.  ... 
doi:10.21742/ijmue.2020.15.1.02 fatcat:spsnotbegzajbiebwuuispzzgi

Context-aware Point-of-Interest Recommendation Using Tensor Factorization with Social Regularization

Lina Yao, Quan Z. Sheng, Yongrui Qin, Xianzhi Wang, Ali Shemshadi, Qi He
2015 Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '15  
Point-of-Interest (POI) recommendation is a new type of recommendation task that comes along with the prevalence of locationbased social networks in recent years.  ...  In addition, we fuse users' social relations as regularization terms of the factorization to improve the recommendation accuracy.  ...  CONCLUSION In this paper, we propose a tensor non-negative decomposition based Point-of-Interest (POI) recommendation approach using users' social constraints as regularization.  ... 
doi:10.1145/2766462.2767794 dblp:conf/sigir/YaoSQWSH15 fatcat:rpc3rfcafrfvnmuephuebjes3u

Linked Open Data in Location-Based Recommendation System on Tourism Domain: a survey

Phatpicha Yochum, Liang Chang, Tianlong Gu, Manli Zhu
2020 IEEE Access  
This work aims not only to present a systematic review and mapping of the linked open data in location-based recommendation system on tourism domain, but also to provide an overview of the current research  ...  In the tourism domain, many studies are using linked open data to address the problem of location-based recommendation by integrating data with other linked open datasets to enrich data and tourism content  ...  [173] studied the problems of user interest awareness on user history by using location-based social networks for location recommender.  ... 
doi:10.1109/access.2020.2967120 fatcat:yqwkrko6mzfw5e5kckfaxbxzju
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