Skip to main content
Log in

Ordered matrix representation supporting the visual analysis of associated data

  • Moop
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

References

  1. Chen Y, Du X M, Yuan X R. Ordered small multiple treemaps for visualizing time-varying hierarchical pesticide residue data. Vis Comput, 2017, 33: 1073–1084

    Article  Google Scholar 

  2. Xie C, Chen W, Huang X X, et al. VAET: a visual analytics approach for E-transactions time-series. IEEE Trans Visual Comput Graph, 2014, 20: 1743–1752

    Article  Google Scholar 

  3. Page L, Brin S, Motwani R, et al. The PageRank Citation Ranking: Bringing Order to the Web. Technical Report 1999-66, Stanford InfoLab

  4. Mei H H, Ma Y X, Wei Y T, et al. The design space of construction tools for information visualization: a survey. J Visual Lang Comput, 2018, 44: 120–132

    Article  Google Scholar 

  5. Du X M, Chen Y, Li Y. TransGraph: a transformation-based graph for analyzing relations in data set. J Comput-Aided Des Comput Graph, 2018, 30: 79–89

    Google Scholar 

Download references

Acknowledgments

This work was supported by National Key R&D Program of China (Grant No. 2018YFC1603602), National Natural Science Foundation of China (Grant Nos. 61972010, 61772456, 61761136020), and Basic Research Project of the Ministry of Science and Technology (Grant No. 2015FY111200).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi Chen.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, Y., Lv, C., Li, Y. et al. Ordered matrix representation supporting the visual analysis of associated data. Sci. China Inf. Sci. 63, 184101 (2020). https://doi.org/10.1007/s11432-019-2647-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-019-2647-3

Navigation