---
_id: '7213'
abstract:
- lang: eng
  text: 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.
alternative_title:
- SCI
article_processing_charge: No
author:
- first_name: Sumit
  full_name: Bhatia, Sumit
  last_name: Bhatia
- first_name: Bapi
  full_name: Chatterjee, Bapi
  id: 3C41A08A-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-2742-4028
- first_name: Deepak
  full_name: Nathani, Deepak
  last_name: Nathani
- first_name: Manohar
  full_name: Kaul, Manohar
  last_name: Kaul
citation:
  ama: '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>'
  apa: '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>'
  chicago: 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>.
  ieee: 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.
  ista: '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.'
  mla: 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>.
  short: S. Bhatia, B. Chatterjee, D. Nathani, M. Kaul, in:, Complex Networks and
    Their Applications VIII, Springer Nature, 2020, pp. 27–39.
conference:
  end_date: 2019-12-12
  location: Lisbon, Portugal
  name: 'COMPLEX: International Conference on Complex Networks and their Applications'
  start_date: 2019-12-10
date_created: 2019-12-29T23:00:45Z
date_published: 2020-01-01T00:00:00Z
date_updated: 2024-02-22T13:16:06Z
day: '01'
ddc:
- '004'
department:
- _id: DaAl
doi: 10.1007/978-3-030-36687-2_3
ec_funded: 1
external_id:
  isi:
  - '000843927300003'
file:
- access_level: open_access
  checksum: 8951f094c8c7dae9ff8db885199bc296
  content_type: application/pdf
  creator: bchatter
  date_created: 2020-10-08T08:16:48Z
  date_updated: 2020-10-08T08:16:48Z
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  file_name: main.pdf
  file_size: 310598
  relation: main_file
  success: 1
file_date_updated: 2020-10-08T08:16:48Z
has_accepted_license: '1'
intvolume: '       881'
isi: 1
language:
- iso: eng
month: '01'
oa: 1
oa_version: Submitted Version
page: 27-39
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
publication: Complex Networks and their applications VIII
publication_identifier:
  eissn:
  - '18609503'
  isbn:
  - '9783030366865'
  issn:
  - 1860949X
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: A persistent homology perspective to the link prediction problem
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 881
year: '2020'
...