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An Integrated Framework for Friend Recommender System based on Graph Theoretic Approach
unpublished
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an efficient Friend Suggestion Recommender System. ...
This paper discusses about various ways of graph theoretic representations of OSN including structure-based and content or interaction-based approaches. ...
An Integrated Framework for Friend Recommender System based on GTA R.Ganguli et al. ...
doi:10.29007/4bwn
fatcat:cnltor4t75ey3nallhw5ipqdee
Do You Have a Pop Face? Here is a Pop Song. Using Profile Pictures to Mitigate the Cold-start Problem in Music Recommender Systems
2015
ACM Conference on Recommender Systems
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Music listening can be regarded as a social activity, in which people can listen together and make friends with one other. ...
However, utilizing the information for recommendation could be difficult, because such information is usually sparse. ...
For the specific application of music recommendation, we propose 3 different ways to construct such a social graph: • Social graph: Build the graph only based on users' friends, which will enable DeepWalk ...
dblp:conf/recsys/ChenCLTY15
fatcat:a4qxecgx3zhapglddb2p722ewm
The Era of Intelligent Recommendation: Editorial on Intelligent Recommendation with Advanced AI and Learning
2020
IEEE Intelligent Systems
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/October issue of IEEE Intelligent Systems (IS). ...
Sydney & IT IS OUR pleasure to share with you this special issue on intelligent recommendation with advanced artificial intelligence (AI) and learning, which includes eight articles published in the September ...
The first article entitled "MGNN: Mutualistic Graph Neural Network for Joint Friend and Item Recommendation" by Xiao et al. 4 proposes a holistic approach to predict users' preferences on friends and ...
doi:10.1109/mis.2020.3026430
fatcat:4myxztm6bzexlc6z7fffddnnk4
A Framework to Formulate Customer Taste from Unstructured Review Data
2016
Procedia Computer Science
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This paper describes the framework and explains a specific use case such as recommendation system deriving value out of it. ...
The proposed framework addresses the blind spot in the current techniques of content based recommendation that works well for businesses selling products such as televisions or personal computers but does ...
The most famous of the graph theoretical approaches is Textrank 19 . ...
doi:10.1016/j.procs.2016.07.308
fatcat:dpq2lpktjng5lfk35qb2ei74nq
Expert recommendation based on social drivers, social network analysis, and semantic data representation
2011
Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems - HetRec '11
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Knowledge networks and recommender systems are especially important for expert finding within organizations and scientific communities. ...
Useful recommendation of experts, however, is not an easy task for many reasons: It requires reasoning about multiple complex networks from heterogeneous sources (such as collaboration networks of individuals ...
The Multitheoretical, Multilevel (MTML) analytic framework provides a coherent, overarching framework for integrating conceptual, theoretical, and empirical work. ...
doi:10.1145/2039320.2039326
fatcat:onoxqzzfdraj7pnfnjxd7sdt64
With a Little Help from My Friends (and Their Friends): Influence Neighborhoods for Social Recommendations
2019
The World Wide Web Conference on - WWW '19
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Social recommendations have been a very intriguing domain for researchers in the past decade. ...
The main premise is that the social network of a user can be leveraged to enhance the rating-based recommendation process. ...
A common approach is to enhance model-based recommender systems with social connections, again most often expressed as trust. ...
doi:10.1145/3308558.3313745
dblp:conf/www/GulatiE19
fatcat:6wca2xodbzcp7l7syvo7bkvccy
Recommendation system using a deep learning and graph analysis approach
[article]
2021
arXiv
pre-print
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In this paper, we have proposed a novel recommendation method based on Matrix Factorization and graph analysis methods. ...
Recommender systems are the techniques for massively filtering information and offering the items that users find them satisfying and interesting. ...
In this paper, we propose a MF-based approach to a CF recommender system based on a combination of graph analysis and deep learning techniques. ...
arXiv:2004.08100v8
fatcat:olpgxe5u5zg3tphqbofgdfilmu
Privacy in Social Media: Identification, Mitigation and Applications
[article]
2018
arXiv
pre-print
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attribute disclosure, 4) user location and privacy, and 5) recommender systems and privacy issues. ...
Users privacy in social media is an emerging task and has attracted increasing attention in recent years. ...
ACKNOWLEDGMENTS The authors would like to thank Alexander Nou for his help throughout the paper. ...
arXiv:1808.02191v1
fatcat:grcar6kx7nbqlf7o3ygrn4te44
An Application of UTAUT2 on Social Recommender Systems: Incorporating Social Information for Performance Expectancy
2014
2014 47th Hawaii International Conference on System Sciences
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We developed a UTAUT2-based framework and tested it in a quantitative study with 266 participants. ...
However, the UTAUT2's applicability and the explanation of performance expectancy for social recommender systems are still unclear. ...
Based on a review of about 80 recommender systems and social recommender systems articles, three central and relevant characteristics were identified for this framework. ...
doi:10.1109/hicss.2014.409
dblp:conf/hicss/OechsleinFH14
fatcat:27x6myxao5g6nmqil45mxnyooe
Behavior analysis in social networks: Challenges, technologies, and trends
2016
Neurocomputing
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Acknowledgement We thank the reviewers for their great efforts. Their professional evaluations and constructive comments are vital for securing the high quality of the special issue. ...
The first paper, "An Intelligent Movie Recommendation System through Group-level Sentiment Analysis in Microblogs", introduces a movie recommendation approach that mines user preferences information embedded ...
It defines the friend increasing speed ranking problem in a semi-supervised framework, and then proposes a partially labeled ranking factor graph model to infer the ranking list of friends increasing speed ...
doi:10.1016/j.neucom.2016.06.008
fatcat:x5mumxc3orduxewwvwsdxdar54
Social-Networks Connect Services
2010
Computer
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Adequate data integrity controls for social plug-ins remain an open research challenge. ...
The Recommendations plug-in allows users to suggest or recommend content on the third-party site. The Activity Feed plug-in shows Facebook users what their friends like. ...
doi:10.1109/mc.2010.239
fatcat:p7cdho6gbjc7lge7b2zrfihf64
Extending trust management with cooperation incentives: a fully decentralized framework for user-centric network environments
2015
Journal of Trust Management
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Our results obtained through simulation prove that the values for bootstrapping and data depletion times are well inside acceptable ranges, given that the total user base for the framework in the world ...
is big enough while using friend-of-a-friend chains. ...
A credit-based recommendation exchange is proposed in order to provide incentives for honest participation in P2P reputation systems where payments for recommendations are based on the trustworthiness ...
doi:10.1186/s40493-015-0018-0
fatcat:bemrkcjefnhbldye7j5uopicy4
Adaptive E-Learning System Based On Learning Interactivity
2014
International journal of computer networks and communications security
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In this paper we propose an improved E-Learning Social Network Exploiting Approach based on clustering algorithm and graph model, which can automatically group distributed e-learners with similar interests ...
Through similarity discovery, trust weights update and potential friends adjustment, the algorithm implements an automatic adapted trust relationship with gradually enhanced satisfactions. ...
The new theoretical perspectives for Internet-based learning are quickly expanding the boundaries and structures for the on/off campus learning process [5] . ...
doi:10.47277/ijcncs/2(3)2
fatcat:adf2aqcw6bgfdblq7nmefaed44
Using Matrix Exponentials for Abstract Argumentation
2016
Computational Models of Argument
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edges should not be accepted together, and empirically evaluate this approach on benchmark graphs from ICCMA'15. ...
Finally, we evaluate postulates for ranking-based argumentation semantics for our approach. ...
purposes and develop a new solver for abstract argumentation based on our approach. ...
dblp:conf/comma/CoreaT16
fatcat:6i5msekifzbn7o47zqrvf2jxx4
Social Recommendation Using Low-Rank Semidefinite Program
2011
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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Differently from the previous approaches, that are based on the conventional gradient descent optimization, we formulate the presented graph Laplacian regularized social recommendation problem into a low-rank ...
The most critical challenge for the recommendation system is to achieve the high prediction quality on the large scale sparse data contributed by the users. ...
Acknowledgments The work was fully supported by Program for New Century Excellent Talents in University (NCET-09-0685) and Fundamental Research Funds for the Central Universities. ...
doi:10.1609/aaai.v25i1.7837
fatcat:5zeszfeucfdevnzg6z6bycm6hy
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