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Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction

Hongxu Chen, Hongzhi YIN, Xiangguo Sun, Tong Chen, Bogdan Gabrys, Katarzyna Musial
2020 Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining  
However, existing methods either heavily rely on high-quality user generated content (including user profiles) or suffer from data insufficiency problem if only focusing on network topology, which brings  ...  based parallel training and account matching across different social networks.  ...  In Facebook-Twitter, 328,224 aligned user pairs are identified across two networks.  ... 
doi:10.1145/3394486.3403201 fatcat:jx7gb6a4vnfo5d6e2kkuc3m5cq

GRAPHYP: A Scientific Knowledge Graph with Manifold Subnetworks of Communities. Detection of Scholarly Disputes in Adversarial Information Routes [article]

Renaud Fabre
2022 arXiv   pre-print
The manifold of practices is expressed from metrics of differentiated uses by triplets of nodes shaped into symmetrical graph subnetworks, with the following three parameters: Mass, Intensity, and Variety  ...  Users are detected from the variety of their search practices and classified in "Cognitive communities" from the analysis of the search history of their logs of scientific documentation.  ...  A notebook describing the test procedure (subsection 3.3), is available as a supplementary file on Github:  ... 
arXiv:2205.01331v1 fatcat:ip7ztag54jfkzbgx53f7rz5vtm

Visual Analytics for Temporal Hypergraph Model Exploration [article]

Maximilian T. Fischer, Devanshu Arya, Dirk Streeb, Daniel Seebacher, Daniel A. Keim, Marcel Worring
2020 IEEE Transactions on Visualization and Computer Graphics   accepted
Many processes, from gene interaction in biology to computer networks to social media, can be modeled more precisely as temporal hypergraphs than by regular graphs.  ...  We facilitate a focused analysis of relevant connections and groups based on interactive user-steering for filtering and search tasks, a dynamically modifiable partition hierarchy, various matrix reordering  ...  Hypergraphs are often drawn as regular graph networks or bipartite networks.  ... 
doi:10.1109/tvcg.2020.3030408 pmid:33048721 arXiv:2008.07299v2 fatcat:z7oqyqam3nggtblulazf7gq724

Beyond networks: Aligning qualitative and computational science studies

Alberto Cambrosio, Jean-Philippe Cointet, Alexandre Hannud Abdo
2020 Quantitative Science Studies  
Focusing on the availability of advanced network structure analysis tools and Natural Language Processing workflows, we interrogate the fault lines between the increasing offer of computational tools in  ...  DATA AVAILABILITY This is a position paper, not an article based on original data.  ...  FUNDING INFORMATION Research for this paper was made possible by a grant from the Canadian Institutes of Health Research (MOP-142478).  ... 
doi:10.1162/qss_a_00055 fatcat:7kmcnsegnvg7nhhu3nk3hdwnpu

Towards Improving Embedding Based Models of Social Network Alignment via Pseudo Anchors

Zihan Yan, Li Liu, Xin Li, William Cheung, Youmin Zhang, Qun Liu, Guoyin Wang
2021 IEEE Transactions on Knowledge and Data Engineering  
Social network alignment aims at aligning person identities across social networks.  ...  The proposed intervention via the use of pseudo anchors and meta-learning allows the learning framework to be applicable to a wide spectrum of network alignment methods.  ...  CONE-Align [38] uses a multi-granularity strategy for the alignment via mapping of the graph structure and users. Instead of aligning the users one by one, Li et al.  ... 
doi:10.1109/tkde.2021.3127585 fatcat:r2tvcvqubzc5xbjo2xwmib266m

Context-Aware Hypergraph Modeling for Re-identification and Summarization

Santhoshkumar Sunderrajan, B. S. Manjunath
2016 IEEE transactions on multimedia  
The proposed algorithm is validated on a wide-area camera network consisting of ten cameras on bike paths.  ...  A hypergraph representation is used to link related objects for search and re-identification. A diverse hypergraph ranking technique is proposed for person-focused network summarization.  ...  person-focussed non-redundant snapshots across the network.  ... 
doi:10.1109/tmm.2015.2496139 fatcat:vpnool2wfzdgvdhppf53jagx2y

Domain-adversarial Network Alignment [article]

Huiting Hong, Xin Li, Yuangang Pan, Ivor Tsang
2019 arXiv   pre-print
Many existing works leverage on representation learning to accomplish this task without eliminating domain representation bias induced by domain-dependent features, which yield inferior alignment performance  ...  Experiments on three real-world social network datasets demonstrate that our proposed approaches achieve state-of-the-art alignment results.  ...  [18] proposed a shallow model MAH to align the network manifolds by modeling social graphs with hypergraphs. e manifolds of social networks are projected onto a common embedded space, then the user mapping  ... 
arXiv:1908.05429v1 fatcat:hupxtj4r2rh7pburrj5ymfj6ci

Transductive Multi-View Zero-Shot Learning

Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong
2015 IEEE Transactions on Pattern Analysis and Machine Intelligence  
It effectively exploits the complementary information offered by different semantic representations and takes advantage of the manifold structures of multiple representation spaces in a coherent manner  ...  To overcome this problem, a novel heterogeneous multi-view hypergraph label propagation method is formulated for zero-shot learning in the transductive embedding space.  ...  Specifically, we construct the heterogeneous hypergraphs across views to combine/align the different manifold structures so as to enhance the robustness and exploit the complementarity of different views  ... 
doi:10.1109/tpami.2015.2408354 pmid:26440271 fatcat:eazqbmoc6vholji7ke6yyis5wq

Learning Kinematic Structure Correspondences Using Multi-Order Similarities

Hyung Jin Chang, Tobias Fischer, Maxime Petit, Martina Zambelli, Yiannis Demiris
2017 IEEE Transactions on Pattern Analysis and Machine Intelligence  
a combinatorial local motion similarity measure using geodesic distance on the Riemannian manifold.  ...  Our main contributions can be summarised as follows: (i) casting the kinematic structure correspondence problem into a hypergraph matching problem by incorporating multi-order similarities with normalising  ...  Moreover, we are interested in one-to-one mapping for every node of one graph to exactly one node of the other. Thus the network alignment has to be global.  ... 
doi:10.1109/tpami.2017.2777486 pmid:29989982 fatcat:e55c5eqe7jeh5i2pnmw5y5nvea

RLINK: Deep reinforcement learning for user identity linkage

Xiaoxue Li, Yanan Cao, Qian Li, Yanmin Shang, Yangxi Li, Yanbing Liu, Guandong Xu
2020 World wide web (Bussum)  
User identity linkage is a task of recognizing the identities of the same user across different social networks (SN).  ...  Our method makes full use of both the social network structure and the history matched identities, meanwhile explores the long-term influence of processing matching on subsequent decisions.  ...  Acknowledgements The authors would like to thank all the people who have contributed to user identity linkage archive for their selfless work.  ... 
doi:10.1007/s11280-020-00833-8 fatcat:svmepr4fprb47pzgz4rse442s4

RLINK: Deep Reinforcement Learning for User Identity Linkage [article]

Xiaoxue Li, Yanan Cao, Yanmin Shang, Yangxi Li, Yanbing Liu, Jianlong Tan
2019 arXiv   pre-print
User identity linkage is a task of recognizing the identities of the same user across different social networks (SN).  ...  Our method makes full use of both the social network structure and the history matched identities, and explores the long-term influence of current matching on subsequent decisions.  ...  -DeepLink [39] DeepLink employs unbiased random walk to generate embeddings, and then use MLP to map users. -MAG [32] MAG uses manifold alignment on graph to map users across networks.  ... 
arXiv:1910.14273v1 fatcat:rgxhurl4lved5nybf22ymgsbwm

Gaussian Processes on Hypergraphs [article]

Thomas Pinder, Kathryn Turnbull, Christopher Nemeth, David Leslie
2021 arXiv   pre-print
We derive a Matern Gaussian process (GP) on the vertices of a hypergraph.  ...  This enables estimation of regression models of observed or latent values associated with the vertices, in which the correlation and uncertainty estimates are informed by the hypergraph structure.  ...  Multi-class classification on legislation networks In this first section we demonstrate the additional utility that is given from a hypergraph representation by comparing our proposed model to its simpler  ... 
arXiv:2106.01982v1 fatcat:7fopnv3gzbbmpl6ynqo3z63ysm

Identifying Users across Different Sites Using Usernames

Yubin Wang, Tingwen Liu, Qingfeng Tan, Jinqiao Shi, Li Guo
2016 Procedia Computer Science  
Identifying users across different sites is to find the accounts that belong to the same individual.  ...  and habits etc., this paper tries to identify users based on username similarity.  ...  Acknowledgement This work was supported in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No. XDA06030200.  ... 
doi:10.1016/j.procs.2016.05.336 fatcat:hipqsu3mwrd2bla3hpyw4g7nny

Unsupervised Topic Hypergraph Hashing for Efficient Mobile Image Retrieval

Lei Zhu, Jialie Shen, Liang Xie, Zhiyong Cheng
2017 IEEE Transactions on Cybernetics  
Motivated by these observations, we propose a novel unsupervised hashing scheme, called topic hypergraph hashing (THH), to address the limitations.  ...  Index Terms-High-order semantic correlations, mobile image retrieval, topic hypergraph hashing (THH).  ...  [43] proposed a multiview alignment hashing by aligning multimodal features into a joint hashing space. Due to multifeature fusion, MMH can achieve better performance than UMH and CMH.  ... 
doi:10.1109/tcyb.2016.2591068 pmid:28113794 fatcat:544qshpsunhktceq4ipo2zdc2m

Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning [article]

Chaozhuo Li, Senzhang Wang, Zheng Liu, Xing Xie, Lei Chen, Philip S. Yu
2021 arXiv   pre-print
User identity linkage, which aims to link identities of a natural person across different social platforms, has attracted increasing research interest recently.  ...  To address the mentioned limitations, in this paper we propose a novel Noise-aware Semi-supervised Variational User Identity Linkage (NSVUIL) model.  ...  Chen, “Mapping users “Adversarial learning for weakly-supervised social network alignment,” across networks by manifold alignment on hypergraph,” in AAAI, 2014, in AAAI, 2019, pp. 996  ... 
arXiv:2112.07373v1 fatcat:e6zcnwrxifasbdmffrvqzmejiq
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