Name
Affiliation
Papers
LILIAN BERTON
Univ Sao Paulo, Inst Math & Comp Sci, Av Trabalhador Sao Carlense 400,Caixa Postal 668, BR-13560970 Sao Paulo, Brazil
22
Collaborators
Citations 
PageRank 
35
16
7.82
Referers 
Referees 
References 
52
190
83
Search Limit
100190
Title
Citations
PageRank
Year
A Temporal Event Graph Approach and Robustness Analysis for Air Transport Network10.402021
Deep analysis of word sense disambiguation via semi-supervised learning and neural word representations00.342021
Topology and robustness analysis of temporal air transport network00.342020
Identifying Noisy Labels With A Transductive Semi-Supervised Leave-One-Out Filter10.402020
A comparison of graph-based semi-supervised learning for data augmentation00.342020
Word sense disambiguation - an evaluation study of semi-supervised approaches with word embeddings.00.342020
Analysis of label noise in graph-based semi-supervised learning00.342020
Categorizing Online Harassment on Twitter.10.352019
A multi-centrality index for graph-based keyword extraction.30.402019
Car Plate Character Recognition Via Semi-Supervised Learning.00.342019
Cluster Analysis of Homicide Rates in the Brazilian State of Goiás from 2002 to 201400.342018
RGCLI: Robust Graph that Considers Labeled Instances for Semi-Supervised Learning.10.352017
The Impact of Social Curiosity on Information Spreading on Networks.10.362017
Neighborhood graph construction for semi-supervised learning.00.342016
Network Sampling Based on Centrality Measures for Relational Classification.00.342016
Link prediction in graph construction for supervised and semi-supervised learning00.342015
A naïve Bayes model based on overlapping groups for link prediction in online social networks40.402015
Influence Maximization Based on the Least Influential Spreaders.10.362015
Graph construction for semi-supervised learning10.342015
Music Genre Classification Using Traditional and Relational Approaches.10.392014
Informativity-based graph: Exploring mutual kNN and labeled vertices for semi-supervised learning10.362012
Identifying Abnormal Nodes In Complex Networks By Using Random Walk Measure00.342010