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An Evolutionary Analysis of DBpedia Datasets

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Web Information Systems and Applications (WISA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11242))

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Abstract

Linked Data, a method to publish interrelated data on the Semantic Web, has rapidly developed in recent years due to new techniques which enhance the availability of knowledge. As one of the most important central hubs of Linked Data, DBpedia is a large crowd-sourcing encyclopedia that contains diverse and multilingual knowledge from various domains in terms of RDF. Existing research has mostly focused on the basic characteristics of a specific version of the DBpedia datasets. Currently, we are not aware of any evolutionary analysis to understand the changes of DBpedia versions comprehensively. In this paper, we first present an overall evolutionary analysis in graph perspective. The evolution of DBpedia has been clarified based on the comparison of 6 versions of the datasets. Then we select two specific domains as subgraphs and calculate a series of metrics to illustrate the changes. Additionally, we carry out an evolutionary analysis of the interlinks between DBpedia and other Linked Data resources. According to our analysis, we find that although the growth of knowledge in DBpedia is an overall trend in recent five years, there does exist quite a few counter-intuitive results.

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Notes

  1. 1.

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References

  1. Bizer, C., Heath, T., Berners-Lee, T.: Linked data-the story so far. Int. J. Semant. Web Inf. Syst. 5(3), 1–22 (2009)

    Article  Google Scholar 

  2. Ceccarello, M., Pietracaprina, A., Pucci, G., et al.: Space and time efficient parallel graph decomposition, clustering, and diameter approximation. In: SPAA 2015, pp. 182–191 (2015)

    Google Scholar 

  3. Ge, W., Chen, J., Hu, W., Qu, Y.: Object link structure in the semantic web. In: Aroyo, L., et al. (eds.) ESWC 2010. LNCS, vol. 6089, pp. 257–271. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13489-0_18

    Chapter  Google Scholar 

  4. Hu, W., Qiu, H., Dumontier, M.: Link analysis of life science linked data. In: Arenas, M., et al. (eds.) ISWC 2015. LNCS, vol. 9367, pp. 446–462. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25010-6_29

    Chapter  Google Scholar 

  5. Jens, L., Robert, I., Max, J., et al.: DBpedia - a large-scale, multilingual knowledge base extracted from wikipedia. Semant. Web J. 6(2), 167–195 (2015)

    Google Scholar 

  6. Klyne, G., Carroll, J.J.: Resource description framework (RDF): concepts and abstract syntax (2006)

    Google Scholar 

  7. Newman, M.: Networks: An Introduction. Oxford University Press, Oxford (2010)

    Book  Google Scholar 

  8. Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. Technical report, Stanford InfoLab (1999)

    Google Scholar 

  9. Rodriguez, M.A.: A graph analysis of the linked data cloud. arXiv preprint arXiv:0903.0194 (2009)

  10. Scott, J.: Social Network Analysis. Sage, Newcastle upon Tyne (2017)

    Google Scholar 

  11. Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: a core of semantic knowledge. In: WWW 2007, pp. 697–706 (2007)

    Google Scholar 

  12. Virkar, Y., Clauset, A.: Power-law distributions in binned empirical data. Ann. Appl. Stat. 8(1), 89–119 (2014)

    Article  MathSciNet  Google Scholar 

  13. Wang, X.F., Chen, G.: Complex networks: small-world, scale-free and beyond. IEEE Circuits Syst. Mag. 3(1), 6–20 (2003)

    Article  Google Scholar 

  14. Watts, D., Strogatz, S.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440–442 (1998)

    Article  Google Scholar 

Download references

Acknowledgement

This work is supported by the National Natural Science Foundation of China (61572353), the Natural Science Foundation of Tianjin (17JCYBJC15400), and the National Training Programs of Innovation and Entrepreneurship for Undergraduates (201710056091).

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Authors and Affiliations

  1. School of Computer Science and Technology, Tianjin University, Tianjin, China

    Weixi Li, Lele Chai, Chaozhou Yang & Xin Wang

  2. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China

    Xin Wang

Authors
  1. Weixi Li
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  2. Lele Chai
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  3. Chaozhou Yang
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  4. Xin Wang
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Corresponding author

Correspondence to Xin Wang .

Editor information

Editors and Affiliations

  1. Renmin University of China, Beijing, China

    Xiaofeng Meng

  2. Huazhong University of Science and Technology, Wuhan, China

    Ruixuan Li

  3. Renmin University of China, Beijing, China

    Kanliang Wang

  4. Taiyuan University of Technology, Yuci, China

    Baoning Niu

  5. Tianjin University, Tianjin, China

    Xin Wang

  6. South China Normal University, Guangzhou, China

    Gansen Zhao

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Li, W., Chai, L., Yang, C., Wang, X. (2018). An Evolutionary Analysis of DBpedia Datasets. In: Meng, X., Li, R., Wang, K., Niu, B., Wang, X., Zhao, G. (eds) Web Information Systems and Applications. WISA 2018. Lecture Notes in Computer Science(), vol 11242. Springer, Cham. https://doi.org/10.1007/978-3-030-02934-0_30

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  • DOI: https://doi.org/10.1007/978-3-030-02934-0_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02933-3

  • Online ISBN: 978-3-030-02934-0

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