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Discriminative Distance-Based Network Indices with Application to Link Prediction [article]

Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem
2018 arXiv   pre-print
Fourth, in order to better motivate the usefulness of our proposed distance measure, we present a novel link prediction method, that uses discriminative distance to decide which vertices are more likely  ...  In this paper, first we develop a new distance measure between vertices of a graph that yields discriminative distance-based centrality indices.  ...  As can be seen in the table, only a very Discriminative Distance-Based Network Indices with Application to Link Prediction , , small sample size, e.g., 0.1% of the number of vertices, is sufficient to  ... 
arXiv:1703.06227v3 fatcat:fiajas7f4betzlq2taxel3hree

SigGAN : Adversarial Model for Learning Signed Relationships in Networks [article]

Roshni Chakraborty, Ritwika Das, Joydeep Chandra
2022 arXiv   pre-print
Existing approaches for link prediction in unsigned networks cannot be directly applied for signed link prediction due to their inherent differences.  ...  Inspired by the recent success of Generative Adversarial Network (GAN) based models which comprises of a discriminator and generator in several applications, we propose a Generative Adversarial Network  ...  Link Prediction Link prediction in signed networks is to identify the sign of an edge.  ... 
arXiv:2201.06437v1 fatcat:rrezslczszdydjcysfzjhl5hby

Generative Adversarial Networks for Spatio-temporal Data: A Survey [article]

Nan Gao, Hao Xue, Wei Shao, Sichen Zhao, Kyle Kai Qin, Arian Prabowo, Mohammad Saiedur Rahaman, Flora D. Salim
2021 arXiv   pre-print
Recently, GAN-based techniques are shown to be promising for spatio-temporal-based applications such as trajectory prediction, events generation and time-series data imputation.  ...  We summarise the application of popular GAN architectures for spatio-temporal data and the common practices for evaluating the performance of spatio-temporal applications with GANs.  ...  And its rival, the Discriminator ( ; ) outputs a single binary value to indicate its prediction of the input's origin.  ... 
arXiv:2008.08903v3 fatcat:pbhxbfgw65bodksjdmwazwo4dq

A bibliometric study on intelligent techniques of bankruptcy prediction for corporate firms

Yin Shi, Xiaoni Li
2019 Heliyon  
This paper aims to explore the application of intelligent techniques in bankruptcy predictions so as to assess its progress and describe the research trend through bibliometric analysis over the last five  ...  The authors sought to contribute to the theoretical development of bankruptcy prediction modeling by bringing new knowledge and key insights.  ...  The authors would like to thank all the reviewers and editors for their many helpful comments and suggestions.  ... 
doi:10.1016/j.heliyon.2019.e02997 pmid:31890956 pmcid:PMC6928309 fatcat:kxevwo2fnbbijejm72fwlxgxxq

Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

Carlo Vittorio Cannistraci, Gregorio Alanis-Lobato, Timothy Ravasi
2013 Bioinformatics  
The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related  ...  protein links.  ...  Trey Ideker for introducing him to the PPI prediction problem, and Dr Alberto Roda for his support in finalizing the article.  ... 
doi:10.1093/bioinformatics/btt208 pmid:23812985 pmcid:PMC3694668 fatcat:xvdcwmwkkfbdvnuzklsh75d3ae

A multilayer approach to multiplexity and link prediction in online geo-social networks

Desislava Hristova, Anastasios Noulas, Chloë Brown, Mirco Musolesi, Cecilia Mascolo
2016 EPJ Data Science  
significantly improve link prediction systems with valuable applications to social bootstrapping and friend recommendations.  ...  Our evaluation, which aims to shed light on the implications of multiplexity for the link generation process, shows that we can successfully predict links across social networking services.  ...  of users based on their interaction on both network layers in order to predict a link across both (a multiplex link).  ... 
doi:10.1140/epjds/s13688-016-0087-z pmid:32355599 pmcid:PMC7175673 fatcat:z3jsbvh4pzaqhlkga7b354csze

Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications

Habib Messai, Muhammad Farman, Abir Sarraj-Laabidi, Asma Hammami-Semmar, Nabil Semmar
2016 Foods  
Predictive models were performed by linear discriminant analysis linking the ordinal weights' triplets (w1, w2, w3) to a set of discriminant FAs.  ...  Predictive models were performed by linear discriminant analysis linking the ordinal weights' triplets (w 1 , w 2 , w 3 ) to a set of discriminant FAs.  ... 
doi:10.3390/foods5040077 pmid:28231172 pmcid:PMC5302435 fatcat:yini6inn7ngn3pi3bhn7nzeawy

Age at maturation predicted from routine scale measurements in Norwegian spring-spawning herring (Clupea harengus) using discriminant and neural network analyses

G Engelhard
2003 ICES Journal of Marine Science  
Similar techniques might well be applicable to any other fish stock with long-term data on scale or otolith growth layers.  ...  Age at maturation predicted from routine scale measurements in Norwegian spring-spawning herring (Clupea harengus) using discriminant and neural network analyses.  ...  The study was supported by the European Research Training Network ModLife (Modern Life History Theory and its Application to the Management of Natural Resources), funded through the Improving Human Potential  ... 
doi:10.1016/s1054-3139(03)00017-1 fatcat:dgljnwc2qjdg5bfzgxp7o5q2rm

Constructing Negative Links from Multi-facet of Social Media

2017 KSII Transactions on Internet and Information Systems  
Additionally, we investigate the ways of solution to general negative link predication problems with CsNL and its extension.  ...  Essentially, high prediction accuracy suggests that negative links are redundant to positive links. Further experiments are performed to evaluate coefficients on different kernels.  ...  sufficient to indicate the existence of negative links.  ... 
doi:10.3837/tiis.2017.05.010 fatcat:3khu2ysz2ffwrp7qsgurhetgou

Place-Based Attributes Predict Community Membership in a Mobile Phone Communication Network

T. Trevor Caughlin, Nick Ruktanonchai, Miguel A. Acevedo, Kenneth K. Lopiano, Olivia Prosper, Nathan Eagle, Andrew J. Tatem, Angel Sánchez
2013 PLoS ONE  
Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of  ...  However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown.  ...  Schill and the Nature Conservancy graciously provided access to the landcover dataset. Author Contributions  ... 
doi:10.1371/journal.pone.0056057 pmid:23451034 pmcid:PMC3579832 fatcat:lyq7oskwrbfujpfg55brbnmo3u

Graph-Based Processing of Macromolecular Information

Cristian R. Munteanu, Vanessa Aguiar-Pulido, Ana Freire, Marcos Martínez-Romero, Ana B. Porto-Pazos, Javier Pereira, Julian Dorado
2015 Current Bioinformatics  
applications dedicated to the calculation of molecular graph topological indices such as S2SNet, CULSPIN and MInD-Prot.  ...  These types of models can predict new drugs, molecular targets and molecular properties of new molecular structures with an important impact on the Drug Discovery, Medicinal Chemistry, Molecular Diagnosis  ...  The best model was validated with an external prediction series with good classification of 80%. The best QSAR model could predict genes and/or proteins linked to the HBC.  ... 
doi:10.2174/1574893610666151008012438 fatcat:yjiexqt7frhl3b7plq3skjcm3q

GANE: A Generative Adversarial Network Embedding [article]

Huiting Hong, Xin Li, Mingzhong Wang
2018 arXiv   pre-print
Experiments with real-world network datasets demonstrate that our models constantly outperform state-of-the-art solutions with significant improvements on precision in link prediction, as well as on visualizations  ...  Wasserstein-1 distance is adopted to train the generator to gain better stability.  ...  The learned representations are then sent to some machine learning toolkits to guide a specific discriminative task, such as link prediction with classification or regression models.  ... 
arXiv:1805.07324v2 fatcat:ujul6yum4ncnlko5kj2hvbvouu

A Classification-Based Approach to Semi-Supervised Clustering with Pairwise Constraints [article]

Marek Śmieja, Łukasz Struski, Mário A. T. Figueiredo
2020 arXiv   pre-print
In this paper, we introduce a neural network framework for semi-supervised clustering (SSC) with pairwise (must-link or cannot-link) constraints.  ...  In contrast to existing approaches, we decompose SSC into two simpler classification tasks/stages: the first stage uses a pair of Siamese neural networks to label the unlabeled pairs of points as must-link  ...  A hard link prediction is obtained by comparing the distance d(x, y) with a threshold T : x and y are classified if d(x, y) 2 < T .  ... 
arXiv:2001.06720v1 fatcat:f5skfv4ycbcgpkjshb3b3jneeu

Efficient link prediction in the protein–protein interaction network using topological information in a generative adversarial network machine learning model

Olivér M. Balogh, Bettina Benczik, András Horváth, Mátyás Pétervári, Péter Csermely, Péter Ferdinandy, Bence Ágg
2022 BMC Bioinformatics  
As machine learning, an image-to-image translation inspired conditional generative adversarial network (cGAN) model utilizing Wasserstein distance-based loss improved with gradient penalty was used, taking  ...  Therefore, here we aimed to offer a novel approach to the link prediction task in PPI networks, utilizing a generative machine learning model.  ...  Acknowledgements The original version of the software presented in this paper was developed for the Protein-Protein Interaction Prediction Challenge organized by the International Network Medicine Consortium  ... 
doi:10.1186/s12859-022-04598-x pmid:35183129 pmcid:PMC8858570 fatcat:m7fjegr3mzcjhjy7fj5qfzum4y

Link Prediction in Complex Networks: A Mutual Information Perspective

Fei Tan, Yongxiang Xia, Boyao Zhu, Wang Zhan
2014 PLoS ONE  
In this paper, we reexamine the role of network topology in predicting missing links from the perspective of information theory, and present a practical approach based on the mutual information of network  ...  Many variants of Common Neighbors have been thus proposed to further boost the discriminative resolution of candidate links.  ...  The efficiency of CAR-based indices in predicting top-ranked candidate links is very high for networks with notable link communities.  ... 
doi:10.1371/journal.pone.0107056 pmid:25207920 pmcid:PMC4160214 fatcat:jhiz5ahat5d7tnxk546frqdupq
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