Predição de Novas Coautorias na Rede Social Acadêmica dos Programas Brasileiros de Pós-Graduação em Ciência da Computação

  • Luciano A. Digiampietri Universidade de São Paulo
  • William T. Maruyama Universidade de São Paulo

Resumo


Este artigo estende um trabalho prévio, apresentando uma técnica de predição de novas coautorias combinando técnicas de inteligência artificial com o estado da arte das métricas de predição de relacionamentos em redes sociais.

Palavras-chave: Predição de Coautorias, Predição de Links, Rede Social Acadêmica

Referências

Cukierski,W., Hamner, B., and Yang, B. (2011). Graph-based features for supervised link prediction. In Neural Networks (IJCNN), The 2011 International Joint Conference on, pages 1237–1244.

da Silva Soares, P. and Bastos Cavalcante Prudencio, R. (2012). Time series based link prediction. In Neural Networks (IJCNN), The 2012 International Joint Conference on, pages 1–7.

de Sa, H. and Prudencio, R. (2011). Supervised link prediction in weighted networks. In Neural Networks (IJCNN), The 2011 International Joint Conference on, pages 2281– 2288.

Digiampietri, L., Mena-Chalco, J., de Jésus Pérez-Alcázar, J., Tuesta, E. F., Delgado, K., and Mugnaini, R. (2012a). Minerando e Caracterizando Dados de Currículos Lattes. In CSBC 2012 - BraSNAM.

Digiampietri, L., Mena-Chalco, J., Silva, G. S., Oliveira, L., Malheiro, A., and Meira, D. (2012b). Dinâmica das Relações de Coautoria nos Programas de Pós-Graduação em Computação no Brasil. In CSBC 2012 - BraSNAM.

Digiampietri, L., Santiago, C., and Alves, C. (2013). Predição de coautorias em redes sociais acadêmicas: um estudo exploratório em ciência da computação. In CSBCBraSNAM 2013.

Digiampietri, L., Teodoro, B., Santiago, C., Oliveira, G., and Araújo, J. (2012c). Um sistema de informação extensível para o reconhecimento automático de libras. In SBSI 2012 - Trilhas Técnicas (Technical Tracks).

Dong, Y., Ke, Q., Rao, J., andWu, B. (2011). Predicting missing links via local feature of common neighbors. In Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on, volume 2, pages 1038–1042.

Dong, Y., Tang, J., Wu, S., Tian, J., Chawla, N., Rao, J., and Cao, H. (2012). Link prediction and recommendation across heterogeneous social networks. In Data Mining (ICDM), 2012 IEEE 12th International Conference on, pages 181–190.

Fire, M., Tenenboim, L., Lesser, O., Puzis, R., Rokach, L., and Elovici, Y. (2011). Link prediction in social networks using computationally efficient topological features. In Privacy, security, risk and trust (passat), 2011 ieee third international conference on and 2011 ieee third international conference on social computing (socialcom), pages 73–80.

Gao, S., Denoyer, L., and Gallinari, P. (2012). Link prediction via latent factor blockmodel. In Proceedings of the 21st International Conference Companion on World Wide Web, WWW ’12 Companion, pages 507–508, New York, NY, USA. ACM.

Guo, J. and Guo, H. (2010). Multi-features link prediction based on matrix. In Computer Design and Applications (ICCDA), 2010 International Conference on, volume 1, pages V1–357–V1–361.

Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., and Witten, I. H. (2009). The WEKA data mining software: an update. SIGKDD Explorations, 11(1):10–18.

Hasan, M. and Zaki, M. (2011). A survey of link prediction in social networks. In Aggarwal, C. C., editor, Social Network Data Analytics, pages 243–275. Springer US.

Hsieh, C.-J., Tiwari, M., Agarwal, D., Huang, X. L., and Shah, S. (2013). Organizational overlap on social networks and its applications. In Proceedings of the 22Nd International Conference on World Wide Web, WWW ’13, pages 571–582, Republic and Canton of Geneva, Switzerland. International World Wide Web Conferences Steering Committee.

Kunegis, J., Preusse, J., and Schwagereit, F. (2013). What is the added value of negative links in online social networks? In Proceedings of the 22Nd International Conference on World Wide Web, WWW ’13, pages 727–736, Republic and Canton of Geneva, Switzerland. International World Wide Web Conferences Steering Committee.

Lin, Z., Yun, X., and Zhu, Y. (2012). Link prediction using benefitranks in weighted networks. In Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01, WI-IAT ’12, pages 423–430, Washington, DC, USA. IEEE Computer Society.

Lu, L. and Zhou, T. (2011). Link prediction in complex networks: A survey. Physica A: Statistical Mechanics and its Applications, 390(6):1150 – 1170.

Makrehchi, M. (2011). Social link recommendation by learning hidden topics. In Proceedings of the Fifth ACM Conference on Recommender Systems, RecSys ’11, pages 189–196, New York, NY, USA. ACM.

Perez, C., Birregah, B., and Lemercier, M. (2012). The multi-layer imbrication for data leakage prevention from mobile devices. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on, pages 813–819.

Quercia, D. and Capra, L. (2009). Friendsensing: Recommending friends using mobile phones. In Proceedings of the Third ACM Conference on Recommender Systems, RecSys ’09, pages 273–276, New York, NY, USA. ACM.

Tian, Y., He, Q., Zhao, Q., Liu, X., and Lee, W.-c. (2010). Boosting social network connectivity with link revival. In Proceedings of the 19th ACM International Conference on Information and Knowledge Management, CIKM ’10, pages 589–598, New York, NY, USA. ACM.

Vasuki, V., Natarajan, N., Lu, Z., and Dhillon, I. S. (2010). Affiliation recommendation using auxiliary networks. In Proceedings of the Fourth ACM Conference on Recommender Systems, RecSys ’10, pages 103–110, New York, NY, USA. ACM.

Zhong, E., Fan, W., Zhu, Y., and Yang, Q. (2013). Modeling the dynamics of composite social networks. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’13, pages 937–945, New York, NY, USA. ACM.
Publicado
01/08/2014
DIGIAMPIETRI, Luciano A.; MARUYAMA, William T.. Predição de Novas Coautorias na Rede Social Acadêmica dos Programas Brasileiros de Pós-Graduação em Ciência da Computação. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 3. , 2014, Brasília. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2014 . p.   243-248. ISSN 2595-6094.

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