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Design of vertex-centric algorithms for pattern recognition on large-scale graphs using asynchronous parallel processing

Grant number: 14/25337-0
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): October 01, 2016
Effective date (End): February 28, 2019
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:José Fernando Rodrigues Júnior
Grantee:Gabriel Perri Gimenes
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Since the birth of web 2.0, users no longer just consume, but are now active creators of content that is going to be consumed by other users. This new dynamic took data generation to a whole new scale, called planetary scale or web scale. Often, this data represents relationships between its elements, such as in social networks, recommendation systems, online boards, email networks, scientific citation networks and others. Therefore, this data can be properly modeled as graphs, which contain properties like weights on its edges, associated texts and dynamic behavior that can be explored. To analyze such graphs, the main approach consists of using distributed processing techniques via computer clusters leading to high costs and techinical complexity that can be prohibitive. So, it is desirable to be able to process planetary scale graphs using only a single computer. To do this, we intend to combine edge and vertex centric iterative processing with discrete matrix processing and text processing techniques aiming to develop an analysis framework capable of recognizing patterns, comprehension and helping with decision making. With such methods we intend to develop new algorithms and systems to solve problems like fraud detection, behavior analysis and sentiment analysis, in a variety of domains.

Matéria(s) publicada(s) na Agência FAPESP sobre a bolsa:
Software detects fraudulent defamation on e-commerce sites 

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SPADON, GABRIEL; DE CARVALHO, ANDRE C. P. L. F.; RODRIGUES-JR, JOSE F.; ALVES, LUIZ G. A. Reconstructing commuters network using machine learning and urban indicators. SCIENTIFIC REPORTS, v. 9, AUG 13 2019. Web of Science Citations: 0.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.