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Collaborative Ranking with Social Relationships for Top-N Recommendations

Dimitrios Rafailidis, Fabio Crestani
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
The reason that we focus on the top of the list is that users mainly see the top-N recommendations, and not the whole ranked list.  ...  In our experiments with a benchmark data set from Epinions, we show that our SCR model performs better than state-of-the-art CR models that either consider social relationships or focus on the ranking  ...  In addition, we compare SCR with MR-BPR 5 [6] , a state-of-the-art method for ranking with social relationships in the recommendation problem.  ... 
doi:10.1145/2911451.2914711 dblp:conf/sigir/RafailidisC16a fatcat:kl2fb6hw4bd63k6dzhwfaflz6a

Semantic link-based Model for User Recommendation in Online community

Abeer Elkorany
Experimental results on real dataset from publication network show that the proposed model for people recommendation outperforms other known techniques in ranking recommended collaborators.  ...  This paper proposes a semantic model for people recommendation in online community.  ...  Motivated by the idea of ranking the items in the right order to get the Top-N recommendation list [7, 11] , potential recommendations list for user u x is assembled and re-ranked according to the intersections  ... 
doi:10.24297/ijct.v11i8.3012 fatcat:xw5qxmpfvrhlrb7kw3jjtezyju

MeSH term explosion and author rank improve expert recommendations

Danielle H Lee, Titus Schleyer
2010 AMIA Annual Symposium Proceedings  
One challenge for scientists is to find appropriate collaborators in their research.  ...  Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank.  ...  ., for providing the data set, and gratefully acknowledge the support of the National Center for Research Resources for this project (grant number UL1 RR024153).  ... 
pmid:21347011 pmcid:PMC3041391 fatcat:4ykpzef2fva37ld2hpqgipcmxi

Video recommendation over multiple information sources

Xiaojian Zhao, Jin Yuan, Meng Wang, Guangda Li, Richang Hong, Zhoujun Li, Tat-Seng Chua
2012 Multimedia Systems  
In particular, one novel source user's relationship strength is inferred through the online social network and applied to recommend videos.  ...  Second, based on multiple ranking lists, a multi-task rank aggregation approach is proposed to integrate these ranking lists to generate a final result for video recommendation.  ...  For example, Jebrin and Williams [26] proposed a new approach to make recommendations based on leaders' credibility in ''Follow the Leader'' model as Top-N recommender by incorporating social network  ... 
doi:10.1007/s00530-012-0267-z fatcat:vu2jxkwobjcshf3evbf4pxwxle

Diversity Balancing for Two-Stage Collaborative Filtering in Recommender Systems

Liang Zhang, Quanshen Wei, Lei Zhang, Baojiao Wang, Wen-Hsien Ho
2020 Applied Sciences  
In addition to using conventional collaborative filtering to predict ratings by exploiting available ratings, the proposed model further considers the social relationships of the user.  ...  A novel ranking strategy is then used to rearrange the list of top-N items while maintaining accuracy by (1) rearranging the area controlled by the threshold and by (2) maximizing popularity while maintaining  ...  Rating Prediction and Top-N Re-Ranking Rating Prediction After ranking the aggregated weights, the top n users with the highest weights are selected as neighbors who participate in the rating prediction  ... 
doi:10.3390/app10041257 fatcat:55kvv3sgrzf25gehhlivewny3m

Social network-based service recommendation with trust enhancement

Shuiguang Deng, Longtao Huang, Guandong Xu
2014 Expert systems with applications  
At present, there emerged some service recommendation systems utilizing influence ranking and collaborative filtering algorithms in service recommendation.  ...  Fortunately, the popularity of social network in nowadays brings a good alternative for service recommendation to avoid those.  ...  RS c m ax is the maximum achievable rank score for consumer c if all future purchases had been at the top of a ranked list [26] .  ... 
doi:10.1016/j.eswa.2014.07.012 fatcat:2qajgyszprbadfpznicuktqwzq

Application of Social Network Metrics to a Trust-Aware Collaborative Model for Generating Personalized User Recommendations [chapter]

Iraklis Varlamis, Magdalini Eirinaki, Malamati Louta
2012 Lecture Notes in Social Networks  
One way to improve the quality of recommendations provided to the members of social networks is to use trustworthy resources.  ...  Such media often serve as platforms for information dissemination and product placement or promotion.  ...  large datasets and/or generate real-time recommendations. , we present the performance curves for the top-3, top-15 and top-30 users.  ... 
doi:10.1007/978-3-7091-1346-2_3 dblp:series/lnsn/VarlamisEL13 fatcat:5qtxrguilned3d6nmng3uhdqci

A Random Walk Based Model Incorporating Social Information for Recommendations [article]

Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff, Pan Hui
2013 arXiv   pre-print
Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system.  ...  More precisely, we construct a directed graph whose nodes consist of items and users, together with item content, user profile and social network information.  ...  Experimental methodology and results We evaluate our results with two popular evaluation metrics for top-k recommendations: recall and percentile.  ... 
arXiv:1208.0787v2 fatcat:7h4pdjo6yve3vhneptcbhpqi5m

A randomwalk based model incorporating social information for recommendations

Shang Shang, Sanjeev R. Kulkarni, Paul W. Cuff, Pan Hui
2012 2012 IEEE International Workshop on Machine Learning for Signal Processing  
Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system.  ...  More precisely, we construct a directed graph whose nodes consist of items and users, together with item content, user profile and social network information.  ...  Experimental methodology and results We evaluate our results with two popular evaluation metrics for top-k recommendations: recall and percentile.  ... 
doi:10.1109/mlsp.2012.6349732 dblp:conf/mlsp/ShangKCH12 fatcat:fzthmck2drdr5kpp6lcfojaw2m

Supporting novel biomedical research via multilayer collaboration networks

Konstantin Kuzmin, Xiaoyan Lu, Partha Sarathi Mukherjee, Juntao Zhuang, Chris Gaiteri, Boleslaw K. Szymanski
2016 Applied Network Science  
Unlike most incremental steps, these collaborations have the potential for leaps in understanding, as they reposition research for novel disease applications.  ...  Specifically, it identifies paths of molecular interactions that connect research topics and hypotheses that would not typically be associated, as the basis for scientific collaboration.  ...  Acknowledgments We would like to thank JoAnne Renz, MSN, RN for carefully reviewing this paper for style and grammar and providing valuable suggestions on making the text a better reading.  ... 
doi:10.1007/s41109-016-0015-y pmid:30533503 pmcid:PMC6245218 fatcat:xif4avvc2nbq3kc6hycrr5jtte

Collaborative User Network Embedding for Social Recommender Systems [chapter]

Chuxu Zhang, Lu Yu, Yan Wang, Chirag Shah, Xiangliang Zhang
2017 Proceedings of the 2017 SIAM International Conference on Data Mining  
To address these issues, we propose to extract implicit and reliable social information from user feedbacks and identify top-k semantic friends for each user.  ...  Third, an active user can be socially connected with others who have different taste/preference. Direct usage of explicit social links may mislead recommendation.  ...  Semantic Social Recommender Systems We next introduce how to incorporate top-k semantic friends into low-rank matrix factorization (MF) for ratings prediction, and into Bayesian personalized ranking (BPR  ... 
doi:10.1137/1.9781611974973.43 dblp:conf/sdm/ZhangYWSZ17 fatcat:flzmknehabaindfsgkrpiisl3e

Augmenting Collaborative Recommenders by Fusing Social Relationships: Membership and Friendship [chapter]

Quan Yuan, Li Chen, Shiwan Zhao
2012 Intelligent Systems Reference Library  
In this paper, we explore the role of two types of social relationships: membership and friendship, while being fused with traditional CF (Collaborative Filtering) recommender methods in order to more  ...  Indepth analysis on the experimental data particularly shows the significant improvement by up to 8% on recommendation accuracy, by embedding social relationships in CF via graph model.  ...  The score measures the average (on all users) of the proportion (in percentages) of artists from the testing sets that appear among the top n ranked list from the training sets, for some given n.  ... 
doi:10.1007/978-3-642-25694-3_8 fatcat:qkjm2bhiknho7beojzkia7wg4y

The Collaborative Filtering Method Based on Social Information Fusion

Hao Wang, Yadi Song, Peng Mi, Jianyong Duan
2019 Mathematical Problems in Engineering  
Our method first uses social information fusion to search for similar users and then updates the user rating of items for recommendation using similar users.  ...  Nowadays, abundant social information is produced by the Internet, such as user profiles, social relationships, behaviors, interests, and so on.  ...  Recently, a linear sparse and low-rank representation of the user-item matrix has been applied to produce Top-N recommendations.  ... 
doi:10.1155/2019/9387989 fatcat:lsmm6uzdcfcmvok55o5ahhsxbq


Jing Li, Feng Xia, Wei Wang, Zhen Chen, Nana Yaw Asabere, Huizhen Jiang
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
We propose a random walk model using three academic metrics as basics for recommending new collaborations.  ...  In this paper, we satisfy the demand of collaboration recommendation through co-authorship in an academic network.  ...  When Academic RWR ends, we can generate a top N recommendation list.  ... 
doi:10.1145/2567948.2579034 dblp:conf/www/LiXWCAJ14 fatcat:3sqhiubepndzrk4rcwk6oehq2m

Social Commerce Hybrid Product Recommender

Rahul Hooda, Kulvinder Singh, Sanjeev Dhawan
2014 International Journal of Computer Applications  
This paper explores a very specific instance of Semantic Web -Social Recommender System.  ...  This paper discusses the likelihood of converting social data into quantitative information and using this information to power social recommendations.  ...  Levi's friends store provides peer recommendations.  Increase relationships with others who share your taste: Social commerce enables customers to build relationships with other customers with whom they  ... 
doi:10.5120/17581-8419 fatcat:hi5hl232r5bpxe6rylmmmqybcq
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