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Computationally efficient link prediction in a variety of social networks

Michael Fire, Lena Tenenboim-Chekina, Rami Puzis, Ofrit Lesser, Lior Rokach, Yuval Elovici
2013 ACM Transactions on Intelligent Systems and Technology  
As a result, new interdisciplinary research directions have emerged in which social network analysis methods are applied to networks containing hundreds of millions of users.  ...  They may also be used for exposing hidden links in online social networks.  ...  We achieved this by defining a set of computationally efficient features and extracting them from ten real social network datasets.  ... 
doi:10.1145/2542182.2542192 fatcat:taoztgkgzfem3hd4ckhozdehri

A Survey on Link Prediction Problem in Social Networks

Abhay Kumar Rai
2017 International Journal for Research in Applied Science and Engineering Technology  
Link prediction is a crucial task in analysis of online social networks. It can be used for friend recommendations in social networks.  ...  So, more time efficient and accurate link prediction algorithms are required which can be used for predicting missing links in large size social networks.  ...  This problem is generally known as the link prediction problem. Link prediction has a wide variety of application areas. In the area of social networks, it can be used for friend recommendations.  ... 
doi:10.22214/ijraset.2017.9271 fatcat:ni3uuitkgjd5bdkxjsnfklcqd4

Declarative analysis of noisy information networks

Walaa Eldin Moustafa, Galileo Namata, Amol Deshpande, Lise Getoor
2011 2011 IEEE 27th International Conference on Data Engineering Workshops  
There is a growing interest in methods for analyzing data describing networks of all types, including information, biological, physical, and social networks.  ...  In this paper, we present the architecture of a data management system that enables efficient, declarative analysis of large-scale information networks.  ...  Acknowledgements: This work was supported in part by NSF under Grants IIS-0546136 and IIS-0916736.  ... 
doi:10.1109/icdew.2011.5767619 dblp:conf/icde/MoustafaNDG11 fatcat:5v7h4hmp3rbglits2j2kh3effi

Scalable proximity estimation and link prediction in online social networks

Han Hee Song, Tae Won Cho, Vacha Dave, Yin Zhang, Lili Qiu
2009 Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference - IMC '09  
Proximity measures quantify the closeness or similarity between nodes in a social network and form the basis of a range of applications in social sciences, business, information technology, computer networks  ...  based on past snapshots of a social network.  ...  We also thank Alan Mislove and Krishna Gummadi for sharing their online social network datasets.  ... 
doi:10.1145/1644893.1644932 dblp:conf/imc/SongCDZQ09 fatcat:ee3x6nqqpbefrcjo5ajfw4vzaq

Multi-Scale Link Prediction [article]

Donghyuk Shin, Si Si, Inderjit S. Dhillon
2012 arXiv   pre-print
In this paper, we propose Multi-Scale Link Prediction (MSLP), a framework for link prediction, which can handle massive networks.  ...  The basis idea of MSLP is to construct low rank approximations of the network at multiple scales in an efficient manner.  ...  A key application for proximity measure in social networks is link prediction, which is a key problem in social network analysis [14, 22] .  ... 
arXiv:1206.1891v1 fatcat:aoehmkmjlnewdib3i3nm4db4b4

Deep Learning for Link Prediction in Dynamic Networks Using Weak Estimators

Carter Chiu, Justin Zhan
2018 IEEE Access  
Link prediction is the task of evaluating the probability that an edge exists in a network, and it has useful applications in many domains.  ...  Recent research has focused on extending link prediction to a dynamic setting, predicting the creation and destruction of links in networks that evolve over time.  ...  Under the sponsorship of these grants, we have produced the list of publications [33] , [34] , [35] , [36], [37], [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] , [47] , [48  ... 
doi:10.1109/access.2018.2845876 fatcat:lknrc2sy2jdphdwzq4w5b76ose

Efficient Data Retrieval using Combine Approach of SOM and K-Mean Clustering

Deepa Sharma
2016 International Journal of Computer Applications  
Emergence of recent techniques for scientific knowledge collection has resulted in large scale accumulation of information relating various fields.  ...  This paper proposes a technique for creating knowledge retrieval more practical and efficient using som with K mean clustering technique, So as to get better clustering with reduced quality.  ...  Other samples of mining social networks are link prediction, namely exploitation the options intrinsic of the present model of a social network to model future connections inside the network.  ... 
doi:10.5120/ijca2016911183 fatcat:ammugb7wbfdk5gnj7g7iazie6y

Multi-scale link prediction

Donghyuk Shin, Si Si, Inderjit S. Dhillon
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
In this paper, we propose Multi-Scale Link Prediction (MSLP), a framework for link prediction, which can handle massive networks.  ...  Link prediction, in turn, is an important application of proximity estimation.  ...  An important application of proximity estimation in social networks is link prediction, which is a key problem in social network analysis [15, 23] .  ... 
doi:10.1145/2396761.2396792 dblp:conf/cikm/ShinSD12 fatcat:fmol4eyzxrcbbdenrbw2lakw3y

Clustered embedding of massive social networks

Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu
2012 Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems - SIGMETRICS '12  
, missing link inference, and link prediction.  ...  A central concept in the analysis of social networks is a proximity measure, which quantifies the closeness or similarity between nodes in a social network.  ...  Acknowledgments: This research is supported in part by NSF grants CCF-0916309 and CCF-1117009. We thank Vijay Erramilli and anonymous reviewers for their valuable comments.  ... 
doi:10.1145/2254756.2254796 dblp:conf/sigmetrics/SongSCDLDZQ12 fatcat:wa6jnlkpqfaypjo4l47xa3rbuu

Clustered embedding of massive social networks

Han Hee Song, Berkant Savas, Tae Won Cho, Vacha Dave, Zhengdong Lu, Inderjit S. Dhillon, Yin Zhang, Lili Qiu
2012 Performance Evaluation Review  
, missing link inference, and link prediction.  ...  A central concept in the analysis of social networks is a proximity measure, which quantifies the closeness or similarity between nodes in a social network.  ...  Acknowledgments: This research is supported in part by NSF grants CCF-0916309 and CCF-1117009. We thank Vijay Erramilli and anonymous reviewers for their valuable comments.  ... 
doi:10.1145/2318857.2254796 fatcat:pdneff76mzenplvuqlbwlvduzq

A Survey on E-Marketing by Behavioral Analysis in Online Social Network

2017 International Journal of Science and Research (IJSR)  
Online Social Network has become a great platform for many domains. It usually deals with huge amount of data.  ...  Several challenges arise in the process of constructing an efficient recommendation system. Behavioral Analysis plays a major role in suggesting the right products to the customers.  ...  The degree of a node is number of direct links it has with other nodes [6] . We can say a node with highest degree as most active node in the network.  ... 
doi:10.21275/art20164689 fatcat:pyeznuv2rnd3xae4yas4t6c6t4

Predicting Friendship Links in Social Networks Using a Topic Modeling Approach [chapter]

Rohit Parimi, Doina Caragea
2011 Lecture Notes in Computer Science  
One data mining problem of interest for social networks is the friendship link prediction problem.  ...  In the recent years, the number of social network users has increased dramatically.  ...  10% links known, thus, showing the importance of the user profile data, captured by LDA, for link prediction in social networks.  ... 
doi:10.1007/978-3-642-20847-8_7 fatcat:pr45l4gz5jgz7nduw6yveuumae

A Survey of Social Network Analysis Techniques and their Applications to Socially Aware Networking

Sho TSUGAWA
2018 IEICE transactions on communications  
This paper surveys three types of important SNA techniques for socially aware networking: identification of influential nodes, link prediction, and community detection.  ...  Then, this paper introduces how SNA techniques are used in socially aware networking and discusses research trends in socially aware networking.  ...  The link prediction scores introduced in this section were obtained from a single snapshot of a social network.  ... 
doi:10.1587/transcom.2017ebi0003 fatcat:wntp6jcq2bgkrlr6iqozrmmeqy

Efficient discovery of overlapping communities in massive networks

Prem K. Gopalan, David M. Blei
2013 Proceedings of the National Academy of Sciences of the United States of America  
By finding communities in a large social network, we can more easily make predictions to individual members about who they might be friends with but are not yet connected to.  ...  For example, in a large social network, a member may be connected to coworkers, friends from school, and neighbors.  ...  D.M.B. is supported by Office of Naval Research Grant N00014-11-1-0651, National Science Foundation CAREER 0745520, BIGDATA IIS-1247664 and The Alfred P. Sloan Foundation.  ... 
doi:10.1073/pnas.1221839110 pmid:23950224 pmcid:PMC3767539 fatcat:nd5ptxrogvd2phlej272noue3m

Enhancing Marine Data Transmission with Socially-Aware Resilient Vessel Networks [article]

Ruobing Jiang, Chao Liu
2022 arXiv   pre-print
To efficiently manage opportunistic vessel-to-vessel (V2V) connections for optimal routing, Social Network Analysis (SNA) on historical vessel interactions is applied for vessel familiarity measurement  ...  In this paper, Resilient Vessel Network (RVN) is proposed to fundamentally enhance BMD transmission.  ...  For the class of link prediction methods measuring attribute similarity, the assumption is that two similar nodes tend to form a link.  ... 
arXiv:2204.11654v1 fatcat:t7xphe6u7naxllphfm52x5uq6a
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