Mostafa Haghir Chehreghani

J. Supercomput., November, 2024

A Review on the Impact of Data Representation on Model Explainability.

[BibT_eX]

[DOI]

ACM Comput. Surv., October, 2024

Disinformation detection using graph neural networks: a survey.

[BibT_eX]

[DOI]

Batool Lakzaei

Alireza Bagheri

Artif. Intell. Rev., March, 2024

LOSS-GAT: Label Propagation and One-Class Semi-Supervised Graph Attention Network for Fake News Detection.

[BibT_eX]

[DOI]

Batool Lakzaei

Alireza Bagheri

CoRR, 2024

Heterophily-Aware Fair Recommendation using Graph Convolutional Networks.

[BibT_eX]

[DOI]

Nemat Gholinejad

CoRR, 2024

Strong Transitivity Relations and Graph Neural Networks.

[BibT_eX]

[DOI]

Yassin Mohamadi

CoRR, 2024

The embeddings world and Artificial General Intelligence.

[BibT_eX]

[DOI]

Cogn. Syst. Res., 2024

Hierarchical Correlation Clustering and Tree Preserving Embedding.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Improving empirical efficiency of CUR decomposition.

[BibT_eX]

[DOI]

Zahra Yaghoobi

J. Supercomput., May, 2023

On using affine sketches for multiple-response dynamic graph regression.

[BibT_eX]

[DOI]

J. Supercomput., March, 2023

A deep comprehensive model for stock price prediction.

[BibT_eX]

[DOI]

Mehdi Salemi Mottaghi

Fatemeh Gholamzadeh Nasrabadi

J. Ambient Intell. Humaniz. Comput., 2023

Content Augmented Graph Neural Networks.

[BibT_eX]

[DOI]

AmirHossein Kashani

Pegah Zahedi

CoRR, 2023

Multilevel User Credibility Assessment in Social Networks.

[BibT_eX]

[DOI]

Mohammad Moradi

CoRR, 2023

Non-uniform Sampling Methods for Large Itemset Mining.

[BibT_eX]

[DOI]

Zahra Moteshaker Arani

Proceedings of the IEEE International Conference on Big Data, 2023

2022

On the theory of dynamic graph regression problem.

[BibT_eX]

[DOI]

Comput. Appl. Math., December, 2022

Half a decade of graph convolutional networks.

[BibT_eX]

[DOI]

Nat. Mach. Intell., 2022

Graph Clustering Using Node Embeddings: An Empirical Study.

[BibT_eX]

[DOI]

Mahdi Ghanbari

Proceedings of the IEEE International Conference on Big Data, 2022

On Using Node Indices and Their Correlations for Fake Account Detection.

[BibT_eX]

[DOI]

Sara Asghari

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Dynamical algorithms for data mining and machine learning over dynamic graphs.

[BibT_eX]

[DOI]

WIREs Data Mining Knowl. Discov., 2021

Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs.

[BibT_eX]

[DOI]

Fundam. Informaticae, 2021

Effectively Counting s-t Simple Paths in Directed Graphs.

[BibT_eX]

[DOI]

CoRR, 2021

Sublinear update time randomized algorithms for dynamic graph regression.

[BibT_eX]

[DOI]

Appl. Math. Comput., 2021

Shallow Node Representation Learning using Centrality Indices.

[BibT_eX]

[DOI]

Masoud Malek

Ehsan Nazerfard

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Learning representations from dendrograms.

[BibT_eX]

[DOI]

Mach. Learn., 2020

Sampling informative patterns from large single networks.

[BibT_eX]

[DOI]

Meriem Bouzbila

Future Gener. Comput. Syst., 2020

Generalized Centrality Aggregation and Exclusive Centrality.

[BibT_eX]

[DOI]

CoRR, 2020

Subsampled Randomized Hadamard Transform for Regression of Dynamic Graphs.

[BibT_eX]

[DOI]

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Sketch-based Randomized Algorithms for Dynamic Graph Regression.

[BibT_eX]

[DOI]

CoRR, 2019

Metropolis-Hastings Algorithms for Estimating Betweenness Centrality.

[BibT_eX]

[DOI]

Proceedings of the Advances in Database Technology, 2019

Adaptive Algorithms for Estimating Betweenness and <i>k</i>-path Centralities.

[BibT_eX]

[DOI]

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018

Nonparametric Feature Extraction from Dendrograms.

[BibT_eX]

[DOI]

CoRR, 2018

Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities.

[BibT_eX]

[DOI]

CoRR, 2018

Discriminative Distance-Based Network Indices with Application to Link Prediction.

[BibT_eX]

[DOI]

Comput. J., 2018

Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Efficient Context-Aware K-Nearest Neighbor Search.

[BibT_eX]

[DOI]

Proceedings of the Advances in Information Retrieval, 2018

DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

An In-depth Comparison of Group Betweenness Centrality Estimation Algorithms.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Upper and lower bounds for the q-entropy of network models with application to network model selection.

[BibT_eX]

[DOI]

Inf. Process. Lett., 2017

Discriminative Distance-Based Network Indices and the Tiny-World Property.

[BibT_eX]

[DOI]

CoRR, 2017

Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks.

[BibT_eX]

[DOI]

CoRR, 2017

2016

A Theory-based Study of Graph Mining ; Een theoretische studie van graph mining.

[BibT_eX]

[DOI]

PhD thesis, 2016

Mining rooted ordered trees under subtree homeomorphism.

[BibT_eX]

[DOI]

Maurice Bruynooghe

Data Min. Knowl. Discov., 2016

Modeling Transitivity in Complex Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Transactional Tree Mining.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

A Framework for Description and Analysis of Sampling-Based Approximate Triangle Counting Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

2014

Mining Rooted Ordered Trees under Homeomorphism.

[BibT_eX]

[DOI]

Maurice Bruynooghe

CoRR, 2014

An Efficient Algorithm for Approximate Betweenness Centrality Computation.

[BibT_eX]

[DOI]

Comput. J., 2014

Effective co-betweenness centrality computation.

[BibT_eX]

[DOI]

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Graph and Network Pattern Mining.

[BibT_eX]

[DOI]

Jan Ramon

Constantin Comendant

Yuyi Wang

Proceedings of the Mining User Generated Content., 2014

2013

Efficient Algorithms for Approximate Triangle Counting

[BibT_eX]

[DOI]

CoRR, 2013

2012

Probabilistic Heuristics for Hierarchical Web Data Clustering.

[BibT_eX]

[DOI]

Comput. Intell., 2012

2011

OInduced: An Efficient Algorithm for Mining Induced Patterns From Rooted Ordered Trees.

[BibT_eX]

[DOI]

IEEE Trans. Syst. Man Cybern. Part A, 2011

Efficiently Mining Unordered Trees.

[BibT_eX]

[DOI]

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2009

Efficient rule based structural algorithms for classification of tree structured data.

[BibT_eX]

[DOI]

Euhanna Ghadimi

Intell. Data Anal., 2009

Density link-based methods for clustering web pages.

[BibT_eX]

[DOI]

Decis. Support Syst., 2009

2008

Improving density-based methods for hierarchical clustering of web pages.

[BibT_eX]

[DOI]

Data Knowl. Eng., 2008

2007

A heuristic algorithm for clustering rooted ordered trees.

[BibT_eX]

[DOI]

Intell. Data Anal., 2007

Attaining Higher Quality for Density Based Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Web Reasoning and Rule Systems, First International Conference, 2007

Clustering Rooted Ordered Trees.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2007

Mining Maximal Embedded Unordered Tree Patterns.

[BibT_eX]

[DOI]