Skip to main content
SpringerLink
Log in

Complex Networks’ Analysis Using an Ontology-Based Approach: Initial Steps

  • Conference paper
Knowledge Science, Engineering and Management (KSEM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8793))

Abstract

This paper presents a new ontology that enables the knowledge-based analysis of complex networks. The purpose of our research was to develop a new approach for the knowledge-based analysis of complex networks based on various network attributes and metrics. Our approach is both easy to use and easy to understand by a human. It facilitates the automated classification of different types of networks. For the creation of this ontology we applied an already known methodology from the scientific literature. The ontology was also enriched with our own developed methods. We applied our ontology to the analysis scenarios of complex networks obtained from real world problems, thus supporting its generality, as well as its usability across domains.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393, 440–442 (1998)

    Article  Google Scholar 

  2. Milgram, S.: The small world problem. Psychology Today 2, 60–67 (1967)

    Google Scholar 

  3. McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: Homophily in social networks. Annual Review of Sociology, 415–444 (2001)

    Google Scholar 

  4. Uschold, M., Gruninger, M.: Ontologies: Principles, methods and applications. The knowledge Engineering Review 11, 93–136 (1996)

    Article  Google Scholar 

  5. Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., et al.: Gene ontology: Tool for the unification of biology. Nature Genetics 25, 25–29 (2000)

    Article  Google Scholar 

  6. Wang, J., Ding, Z., Jiang, C.: An ontology-based public transport query system. In: First International Conference on Semantics, Knowledge and Grid, SKG 2005, pp. 62–62. IEEE (2005)

    Google Scholar 

  7. Luciano, J.S., Andersson, B., Batchelor, C., Bodenreider, O., Clark, T., Denney, C.K., Domarew, C., Gambet, T., Harland, L., Jentzsch, A., et al.: The translational medicine ontology and knowledge base: Driving personalized medicine by bridging the gap between bench and bedside. J. Biomed. Semantics 2, S1 (2011)

    Google Scholar 

  8. Hristea, F., Colhon, M.: Feeding syntactic versus semantic knowledge to a knowledge-lean unsupervised word sense disambiguation algorithm with an underlying naïve bayes model. Fundamenta Informaticae 119, 61–86 (2012)

    MathSciNet  Google Scholar 

  9. Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing? International Journal of Human-computer Studies 43, 907–928 (1995)

    Article  Google Scholar 

  10. Guarino, N.: Formal ontology in information systems: Proceedings of the first international conference (FOIS 1998), Trento, Italy, June 6-8, vol. 46. IOS Press (1998)

    Google Scholar 

  11. Mian, P.G., Falbo, R.D.A.: Supporting ontology development with oded. Journal of the Brazilian Computer Society 9, 57–76 (2003)

    Article  Google Scholar 

  12. Erdős, P., Rényi, A.: On random graphs. Publicationes Mathematicae Debrecen 6, 290–297 (1959)

    MathSciNet  Google Scholar 

  13. Granovetter, M.: The strength of weak ties. American Journal of Sociology 78, l (1973)

    Google Scholar 

  14. Barabási, A.L., et al.: Scale-free networks: A decade and beyond. Science 325, 412 (2009)

    Article  MathSciNet  Google Scholar 

  15. Newman, M.E.: Clustering and preferential attachment in growing networks. Physical Review E 64, 025102 (2001)

    Google Scholar 

  16. Barabási, A.L., Gulbahce, N., Loscalzo, J.: Network medicine: A network-based approach to human disease. Nature Reviews Genetics 12, 56–68 (2011)

    Article  Google Scholar 

  17. Wilson, C.: Searching for saddam: Why social network analysis hasn’t led us to osama bin laden. Slate (February 26, 2010)

    Google Scholar 

  18. Cross, R.L., Singer, J., Colella, S., Thomas, R.J., Silverstone, Y.: The organizational network fieldbook: Best practices, techniques and exercises to drive organizational innovation and performance. John Wiley & Sons (2010)

    Google Scholar 

  19. Radicchi, F.: Who is the best player ever? a complex network analysis of the history of professional tennis. PloS One 6, e17249 (2011)

    Google Scholar 

  20. Noy, N.F., McGuinness, D.L., et al.: Ontology development 101: A guide to creating your first ontology (2001)

    Google Scholar 

  21. Horridge, M., Knublauch, H., Rector, A., Stevens, R., Wroe, C.: A practical guide to building owl ontologies using the protégé-owl plugin and co-ode tools edition 1.0. University of Manchester (2004)

    Google Scholar 

  22. Schank, T., Wagner, D.: Approximating clustering-coefficient and transitivity. Universität Karlsruhe, Fakultät für Informatik (2004)

    Google Scholar 

  23. Lambiotte, R., Delvenne, J.C., Barahona, M.: Laplacian dynamics and multiscale modular structure in networks. arXiv preprint arXiv:0812.1770 (2008)

    Google Scholar 

  24. Boldi, P., Vigna, S.: Axioms for centrality. arXiv preprint arXiv:1308.2140 (2013)

    Google Scholar 

  25. Adamic, L.A., Huberman, B.A.: Power-law distribution of the world wide web. Science 287, 2115–2115 (2000)

    Article  Google Scholar 

  26. Borgatti, S.P., Everett, M.G.: Models of core/periphery structures. Social Networks 21, 375–395 (2000)

    Article  Google Scholar 

  27. Hojman, D.A., Szeidl, A.: Core and periphery in networks. Journal of Economic Theory 139, 295–309 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  28. Krebs, V., Holley, J.: Building smart communities through network weaving. Appalachian Center for Economic Networks (2006), http://www.acenetworks.org (retrieved)

  29. Krebs, V.: Managing the 21st century organization. IHRIM Journal 11, 2–8 (2007)

    Google Scholar 

  30. Lusseau, D.: The emergent properties of a dolphin social network. Proceedings of the Royal Society of London 270, S186–S188 (2003)

    Google Scholar 

  31. Becheru, A.: Agile development methods through the eyes of organisational network analysis. In: Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS 2014), p. 53. ACM (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Craiova, Blvd. Decebal nr. 107, Craiova, 200440, Romania

    Alex Becheru & Costin Bădică

Authors
  1. Alex Becheru
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Costin Bădică
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Knowledge Engineering Research Group, University of Vienna, Währingerstr. 29, 1090, Vienna, Austria

    Robert Buchmann

  2. Faculty of Engineering, Research Center for Sustainable Products and Processes, Lucian Blaga University of Sibiu, 10 Victoriei Blv., 550024, Sibiu, Romania

    Claudiu Vasile Kifor

  3. Department of Computer Science, Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Haidian District, 100044, Beijing, China

    Jian Yu

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Becheru, A., Bădică, C. (2014). Complex Networks’ Analysis Using an Ontology-Based Approach: Initial Steps. In: Buchmann, R., Kifor, C.V., Yu, J. (eds) Knowledge Science, Engineering and Management. KSEM 2014. Lecture Notes in Computer Science(), vol 8793. Springer, Cham. https://doi.org/10.1007/978-3-319-12096-6_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12096-6_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12095-9

  • Online ISBN: 978-3-319-12096-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation