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Cited by 16

The DOI matches its Crossref record.

Unveiling Scholarly Communities over Knowledge Graphs

Vahdati, Sahar, Palma, Guillermo, Nath, Rahul Jyoti, Lange, Christoph, Auer, Sören, Vidal, Maria-Esther·2018·Lecture Notes in Computer Science
DOI 10.1007/978-3-030-00066-0_9
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Crossref · 10.1007/978-3-030-00066-0_9

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Some studies conducted casual and subjective evaluation with survey questions and research questions [70, 74, 76] of the KG structure without using precise evaluation measures.

    “Some studies, for example, conducted a casual and subjective evaluation with the help of survey questions and research questions [70, 74, 76] of the KG structure without using precise evaluation measures.”

    From Scholarly knowledge graphs through structuring scholarly communication: a review (2023) · cites this paper as [76]

Citations

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No references could be resolved yet.

Research works printed but not linked: 13

  1. Buluç, A., Meyerhenke, H., Safro, I., Sanders, P., Schulz, C.: Recent advances in graph partitioning. In: Kliemann, L., Sanders, P. (eds.) Algorithm Engineering. LNCS, vol. 9220, pp. 117–158. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49487-6_4 · DOI
  2. Gaertler, M.: Clustering. In: Brandes, U., Erlebach, T. (eds.) Network Analysis: Methodological Foundations. LNCS, vol. 3418, pp. 178–215. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-31955-9_8 · DOI
  3. Karypis, G., Kumar, V.: A fast and high quality multilevel scheme for partitioning irregular graphs. Sci. Comput. 20, 359–392 (1998)
  4. Kastrin, A., Rindflesch, T.C., Hristovski, D.: Link prediction on the semantic MEDLINE network. In: Džeroski, S., Panov, P., Kocev, D., Todorovski, L. (eds.) DS 2014. LNCS (LNAI), vol. 8777, pp. 135–143. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11812-3_12 · DOI
  5. Le, Q.V., Mikolov, T.: Distributed representations of sentences and documents. CoRR abs/1405.4053 (2014) · arXiv
  6. Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. JASIST 58(7), 1019–1031 (2007) · DOI
  7. Newman, M.E.: Modularity and community structure in networks. Proc. Natl. Acad. Sci. 103(23), 8577–8582 (2006) · DOI · Paper page
  8. Palma, G., Vidal, M.-E., Raschid, L.: Drug-target interaction prediction using semantic similarity and edge partitioning. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 131–146. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11964-9_9 · DOI
  9. Paulheim, H.: Knowledge graph refinement: a survey of approaches and evaluation methods. Semant. Web J. 8(3), 489–508 (2017) · DOI · Paper page
  10. Sachan, M., Ichise, R.: Using semantic information to improve link prediction results in network datasets. IJET 2(4), 334–339 (2010) · DOI
  11. Traverso-Ribón, I., Palma, G., Flores, A., Vidal, M.-E.: Considering semantics on the discovery of relations in knowledge graphs. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds.) EKAW 2016. LNCS (LNAI), vol. 10024, pp. 666–680. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49004-5_43 · DOI
  12. Wang, P., Xu, B., Wu, Y., Zhou, X.: Link prediction in social networks: the state-of-the-art. Sci. China Inf. Sci. 58(1), 1–38 (2015)
  13. Xia, F., Wang, W., Bekele, T.M., Liu, H.: Big scholarly data: a survey. In: IEEE Big Data (2017) · DOI

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Metadata

Authors
Vahdati, S., Palma, G., Nath, R. J., Lange, C., Auer, S., & Vidal, M.-E.
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2018
Pages
103-115
ISSN
  • 0302-9743
  • 1611-3349
DOI
10.1007/978-3-030-00066-0_9
Cited by
16
References
0
Licence
www.springer.com/tdm (unspecified)

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