conference paper published yes Sumit Bhatia author Bapi Chatterjee author 3C41A08A-F248-11E8-B48F-1D18A9856A870000-0002-2742-4028 Deepak Nathani author Manohar Kaul author DaAl department COMPLEX: International Conference on Complex Networks and their Applications ISTplus - Postdoctoral Fellowships project Persistent homology is a powerful tool in Topological Data Analysis (TDA) to capture the topological properties of data succinctly at different spatial resolutions. For graphical data, the shape, and structure of the neighborhood of individual data items (nodes) are an essential means of characterizing their properties. We propose the use of persistent homology methods to capture structural and topological properties of graphs and use it to address the problem of link prediction. We achieve encouraging results on nine different real-world datasets that attest to the potential of persistent homology-based methods for network analysis. https://research-explorer.ista.ac.at/download/7213/8625/main.pdf application/pdfno Springer Nature2020Lisbon, Portugal eng 1860-949X 1860-9503 9783030366865 00084392730000310.1007/978-3-030-36687-2_3 88127-39 Bhatia, Sumit, Bapi Chatterjee, Deepak Nathani, and Manohar Kaul. “A Persistent Homology Perspective to the Link Prediction Problem.” In <i>Complex Networks and Their Applications VIII</i>, 881:27–39. Springer Nature, 2020. <a href="https://doi.org/10.1007/978-3-030-36687-2_3">https://doi.org/10.1007/978-3-030-36687-2_3</a>. Bhatia, Sumit, et al. “A Persistent Homology Perspective to the Link Prediction Problem.” <i>Complex Networks and Their Applications VIII</i>, vol. 881, Springer Nature, 2020, pp. 27–39, doi:<a href="https://doi.org/10.1007/978-3-030-36687-2_3">10.1007/978-3-030-36687-2_3</a>. Bhatia S, Chatterjee B, Nathani D, Kaul M. A persistent homology perspective to the link prediction problem. In: <i>Complex Networks and Their Applications VIII</i>. Vol 881. Springer Nature; 2020:27-39. doi:<a href="https://doi.org/10.1007/978-3-030-36687-2_3">10.1007/978-3-030-36687-2_3</a> S. Bhatia, B. Chatterjee, D. Nathani, and M. Kaul, “A persistent homology perspective to the link prediction problem,” in <i>Complex Networks and their applications VIII</i>, Lisbon, Portugal, 2020, vol. 881, pp. 27–39. Bhatia S, Chatterjee B, Nathani D, Kaul M. 2020. A persistent homology perspective to the link prediction problem. Complex Networks and their applications VIII. COMPLEX: International Conference on Complex Networks and their Applications, SCI, vol. 881, 27–39. Bhatia, S., Chatterjee, B., Nathani, D., &#38; Kaul, M. (2020). A persistent homology perspective to the link prediction problem. In <i>Complex Networks and their applications VIII</i> (Vol. 881, pp. 27–39). Lisbon, Portugal: Springer Nature. <a href="https://doi.org/10.1007/978-3-030-36687-2_3">https://doi.org/10.1007/978-3-030-36687-2_3</a> S. Bhatia, B. Chatterjee, D. Nathani, M. Kaul, in:, Complex Networks and Their Applications VIII, Springer Nature, 2020, pp. 27–39. 72132019-12-29T23:00:45Z2025-07-10T11:54:23Z