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The RR Project — A Framework for Relationship Network Viewing and Management

  • César Stradiotto
  • Everton Pacheco
  • Andre Bortolon
  • Hugo Hoeschl
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 218)

Abstract

The Relationship Networks Project (RR - Redes de Relacionamento) is an innovative project, which intends to create a framework, which allows -through a fast data modeling - implementing interface elements that describe in a clearly visual way, in two-dimensional presentation, a relationship network among heterogeneous items. This environment also allows the machine to do operations over these relations, such as to find paths or sets, to help the implementation of AI algorithms, or data extraction by the final user. Through graph theory, with visual items, it is possible to find elements with specific characteristics and relationships between them, by the application of filters, refining searches inside an extreme large datasets, or showing differentiated connection maps. Two prototypes were created with this framework: A system which allows seeing telephonic calls sets and financial transactions, and a system for ontology viewing for a digital dictionary inside a semantic network. Another software, in prototypical phase, also for semantic network vision, is being constructed. This document will present the basic RR structure, showing and justifying the creation of the two referred software above.

Keywords

Resource Description Framework Semantic Network Financial Transaction United Nations Security Council Security Council Resolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Bibliography

  1. 1.
    GIRVAN, Michelle.; Newman, M. E. J. Community structure in social and biological networks. Base de Dados arXiv.org — 07 dec. 2001. Disponível em: 〈http://arxiv.org/abs/cond-mat/0112110〉 página 2. Acesso em: 12 dez. 2003Google Scholar
  2. 2.
    BARABÁSI, A. L.; BONABEAU, E. Scale-Free Networks. Scientific American, New York. v.1, 7 dec. 2001. Disponível em: 〈http://www.nd.edu/~networks/PDF/Scale-Free%20Sci%20Amer%20May03.pdf〉. p52. Acesso em: 14 Jan. 2004-ISSN 0036-8733.Google Scholar
  3. 3.
    SIQUEIRA, E. Brasil fala 600% mais que em 1994. 24 mar. 2002. O Estado de São Paulo. Disponível em: 〈http://txt.estado.com.br/colunistas/siqueira/2002/03/siqueira020324.html〉. Acesso em: 12 dez. 2003Google Scholar
  4. 4.
    DIAS, J. A. Telefonia Atrairá Investidor Externo. Folha de São Paulo. 11 jan. 2004. Cadeino Folha Dinheiro. Disponível em: 〈http://wwwl.folha.uol.com.br/fsp/dinheiro/fil101200410.htm〉. Acesso em: 12 jan. 2004.Google Scholar
  5. 5.
    LOBATO. E. Fraude Telefônica Fica Mais Sofisticada. 23 nov. 2003. Folha de São Paulo. Caderno Folha Cotidiano. Disponível em 〈http://www1.folha.uol.com.br/fsp/cotidian/ff2311200317.htm〉. Acesso em: 30 nov. 2003.Google Scholar
  6. 6.
    IDGNOW. Cavalos de Tróia crescem 1184% em 2004. http://idgnow.uol.com.br/AdPortalv5/SegurancaInterna.aspx?GUID=4D152F5C-4EB6-4884-9AAE-E301FDFD74E$&ChannelID=21080105IDGNOW\SEGURANÇA\NOTÍCIA Publicado em 2 fevereiro de 2005.Google Scholar
  7. 7.
    FILHO, A.G.P. As contas CC5 e as instituições financeiras internacionais. Portal de Contabilidade. 20 de janeiro de 2006. http://www.cosif.com.br/publica.asp?arquivo=20050407cc5ilegais Acessado em jaileiro de 2006.Google Scholar
  8. 8.
    MCDOWELL, J, NOVIS, G. As Conseqüências da Lavagem de Dinheiro e dos Crimes Financeiros. Perspectivas Econômicas, Maio de 2001 http://usinfo.state.gov/journals/ites/0501/ijep/ie0502.htm Acessado en1 noveinbro de 2005.Google Scholar
  9. 9.
    STRADIOTTO. C. R. K.; BORTOLOX, A,; HOESCHL, H. C.; MARAFON, M. J.. Ferramenta de Desenvolvimento de Software para Representação Visual de Redes de Relacionamento. In: CONGRESSO NACIONAL DE TECNOLOGIA DA INFORMAÇÃO E COMUNICAÇÃO, 2004. http://www.sucesu2005.com.br/palestras2004/24.html Acessado em Janeiro de 2006Google Scholar
  10. 10.
    MENDRONI, M. B. O Sigilo da Fase Pré-Processual. Revista Justitia, pl. São Paulo [2004] Disponível em: 〈http://www.mp.sp.gov.br/justitia/CRIMINAL/crime%2035.pdf〉 Acesso em: jan. 2004.Google Scholar
  11. 11.
    BARRETO, A. S.; BUENO, T. C. D.; HOESCHL, H. C. Applying Case Based Reasoning to Knowledge Representation of Tributary Decisions. In: THE 9th INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW, 2003, Edimburgh. Proceedings... New York: Association for Computer Machinery (ACM) — p. 77. ISBN 1-58113-747-8.CrossRefGoogle Scholar
  12. 12.
    BUENO, T. C. D. et al. Using RBC to Classify Judicial Petitions on e-Court. In: THE 9th INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW, 2003, Edimburgh. Proceedings... New York: Association for Computer Machinery (ACM) — p83. ISBN 1-58113-747-8.CrossRefGoogle Scholar
  13. 13.
    COSTA, F.C.; BUENO T.C.D.; RIBEIRO, E.B.Q. New Procedures for Environmental Licensing with Artificial Intelligence — CIPPLA. In THE 9th INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW, 2003, Edimburgh Proceedings... New York: Association for Computer Machinery (ACM) — p87 ISBN 1-58113-747-8CrossRefGoogle Scholar
  14. 14.
    HOESCHL. H.C. et al. Dynamically Contextualized Knowledge Representation of the United Nations Security Council Resolutions. In: THE 9th INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW, 2003, Edimburgh. Proceedings... New York: Association for Computer Machinery (ACM) — p. 95. ISBN 1-58113-747-8.CrossRefGoogle Scholar
  15. 15.
    HOESCHL. H.C. et al. Knowledge-Based System Applied on the Previous Consent of Brazilian National Defense Council. In: THE 9th INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW, 2003, Edimburgh. Proceedings... New York: Association for Computer Machinery (ACM) — p. 97. ISBN 1-58113-747-8.CrossRefGoogle Scholar
  16. 16.
    MATTOS, E.S. et al. A Knowledge Base for Automatic Capitulation in Expert System. In: THE 9th INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW, 2003, Edimburgh. Proceedings... New York: Association for Computer Machinery (ACM) — p. 99. ISBN 1-55113-747-8.CrossRefGoogle Scholar
  17. 17.
    RDF. Resource Description Framework. Disponível em: 〈http://www.w3.org/RDF/〉. Acesso em: jan. 2004.Google Scholar
  18. 18.
    XU, Z.; WU, J. A Survey Of Knowledge Base Grid For Traditional Chinese Medicine. In: THE FIFTH INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEM, v. 4. Software Agents and Internet Computer, 2003, Angers. Proceedings... Setúbal: Escola Superior de Tecnologia de Setubal. p. 136. ISBN: 972-95816-1-8. Disponível em: 〈http://www.iceis.org〉. Acesso em: 19 jan. 2004.Google Scholar
  19. 19.
    CAWSEY, A. Semantic Nets. Disponível em:〈http://www.cee.hw.ac.uk/~alison/ai3notes/subsection2_4_2_1.html〉, Acesso em: jan. 2004.Google Scholar
  20. 20.
    BUENO T. C. D et al. Knowledge Engineering Suite: a Tool to Create Ontologies for Automatic Knowledge Representation in Knowledge-based Systems. in: The 2nd International Workshop on Natural Language Understanding And Cognitive Science (NLUCS-2005) in ICEIS-7th international conference. Proceedings of 7th International Conference On Enterprise Information Systems. 2005.Google Scholar
  21. 21.
    RIBEIRO, M. S. KMAI: da RC2D à PCE. 2003. 190f. Dissertação (Mestrado em Engenharia de Produção) — Universidade Federal de Santa Catarina, Florianópolis, 2003.Google Scholar

Copyright information

© International Federation for Information Processing 2006

Authors and Affiliations

  • César Stradiotto
    • 1
  • Everton Pacheco
    • 1
  • Andre Bortolon
    • 1
  • Hugo Hoeschl
    • 2
  1. 1.Parque Tecnológieo Alfa, Centro de Tecnologia IlhaSoftWBSA Sistemas Inteligentes SAFlorianópolis, SCBrasil
  2. 2.Instituto de Governo EletrônicoInteligência Jurídica e Sistemas — IJURISFlorianópolis - SCBrasil

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