Um Sistema de Predição de Relacionamentos em Redes Sociais

Digiampietri, Luciano Antônio; Maruyama, William; Santiago, Caio Bispo; Lima, Jamison

doi:10.5753/sbsi.2015.5810

Cited by 7 publications

(6 citation statements)

References 24 publications

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“…The first test case was planned to show the performance of the algorithm in a real area of knowledge. We chose a test case based on a workflow of social network analysis [Digiampietri et al 2014a, Digiampietri et al 2015. This test case has approximately 20 high dependent tasks, alternating between light and heavy loads.…”

Section: Test Case Of Social Network Analysismentioning

confidence: 99%

A volunteer computing system implemented with peer-to-peer communication optimized for small and limited environments

Santiago¹,

Digiampietri²

2018

Anais Do Brazilian E-Science Workshop (BreSci)

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The computational needs of scientific experiments often require powerful computers. One alternative way to obtain this processing power is taking advantage of the idle processing of personal computers as volunteers. This technique is known as volunteer computing and has great potential in helping scientists. However, there are several issues which can reduce the efficiency of this approach when applied to complex scientific experiments, such as, the ones with long processing time, very large input or output data, etc. In order to face these challenges, we designed a volunteer computing system based on peer-to-peer communication. When compared with the local execution of activities and traditional volunteer computing, the execution time was improved and, in some cases, there was also a reduction of the server upload bandwidth use. Scientific experiments, in several cases, are organized as bag-of-tasks [Kwan and Jogesh 2010] or scientific workflows [Medeiros et al. 1996]. Bag-of-tasks are composed of a set of completely independent tasks, what is very different from workflows where a task needs to wait for the conclusion of another task. Both, typically, require huge computational power and a way to obtain it is the use of several personal computers, for example, desktop grids [Kondo et al. 2007, Anderson 2004] or volunteer computing [Anderson and Fedak 2006]. Volunteer computing (VC) projects take idle resources from donors: the tasks are sent to volunteers (in general using the Internet), and they send the results back to a server. This approach may provide a lot of computational power [Anderson 2004], but in scientific experiments, there are many issues which can turn this approach inefficient, such as long processing tasks [Dethier et al. 2008], great volumes of data to be transferred [Duan et al. 2012] or instability in volunteer computers [Dias et al. 2010]. The majority of these issues are related to the low-speed communication with donors across the Internet. The development of this work was based on an extension [Digiampietri et al. 2014b] of the Workflow Management System (WfMS) called WOODSS (A Spatial Decision Support System based on Workflows) [Seffino et al. 1999], an open source system written in Java extended in this project to deal with P2P communication.

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Section: Test Case Of Social Network Analysismentioning

confidence: 99%

A volunteer computing system implemented with peer-to-peer communication optimized for small and limited environments

Santiago¹,

Digiampietri²

2018

Anais Do Brazilian E-Science Workshop (BreSci)

Self Cite

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“…The prediction of relationships within a social network is a task that has gained attention in recent years, because it may helps from finding friends who were not connected in an online social network [Vasuki et al 2010, Tian et al 2010, Perez et al 2012, Fire et al 2011, Zhong et al 2013, Quercia and Capra 2009, to enhance the performance of work in companies or in universities [Hsieh et al 2013, Dong et al 2012, de Sa and Prudencio 2011. In the academic social network context, the link prediction is mainly used for predicting coauthorships, whose purpose is to indicate a pair of researchers that potentially will collaborate in the publication of papers [Guo and Guo 2010, Makrehchi 2011, Dong et al 2011, Gao et al 2012, Lin et al 2012, Digiampietri et al 2013, Digiampietri et al 2015.…”

Section: Introductionmentioning

confidence: 99%

Co-authorship prediction in academic social network

Maruyama

Digiampietri

2016

Anais Do v Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2016)

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The prediction of relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating the most promising partnerships. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents an approach to predict coauthorships combining artificial intelligence techniques with the state-of-the-art metrics for link predicting in social networks.

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“…A predição de novos relacionamentos dentro de uma rede socialé uma tarefa que ganhou bastante destaque nosúltimos anos e serve para, desde encontrar amigos que ainda não estavam ligados em numa rede social online [Vasuki et al 2010, Tian et al 2010, Perez et al 2012, Fire et al 2011, Zhong et al 2013, Quercia and Capra 2009, até para potencializar a realização de trabalhos em empresas ou na academia [Maruyama and Digiampietri 2016, Digiampietri et al 2015, Digiampietri and Maruyama 2014, Digiampietri et al 2013, Hsieh et al 2013, Dong et al 2012, de Sa and Prudencio 2011.…”

Section: Introductionunclassified

Predição de Relacionamentos em Redes Sociais, uma Revisão Sistemática

Maruyama

Digiampietri

2016

Anais Do v Brazilian Workshop on Social Network Analysis and Mining (BraSNAM 2016)

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A área de análise de redes sociais está em ascensão. Uma importante tarefa desta área é a predição de relacionamentos, na qual o objetivo é prever conexões entre usuários. Para a realização desta tarefa são utilizados atributos, métodos, algoritmos e técnicas que medem, de alguma forma, a possibilidade de um relacionamento ser criado. No entanto, existem muitas abordagens e combinações de atributos para predizer relacionamentos. Este trabalho tem como objetivo realizar um levantamento abrangente dos atributos ou características que podem ser utilizados na predição de relacionamentos nos diversos contextos das redes sociais, a partir da metodologia de Revisão Sistemática.

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Um Sistema de Predição de Relacionamentos em Redes Sociais

Cited by 7 publications

References 24 publications

A volunteer computing system implemented with peer-to-peer communication optimized for small and limited environments

A volunteer computing system implemented with peer-to-peer communication optimized for small and limited environments

Co-authorship prediction in academic social network

Predição de Relacionamentos em Redes Sociais, uma Revisão Sistemática

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