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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
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Progresses and challenges in link prediction.

Tao Zhou1

  • 1CompleX Lab, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.

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|November 8, 2021
PubMed
Summary
This summary is machine-generated.

This review explores link prediction in network science, detailing methods like local similarity and network embedding to forecast missing connections. It highlights recent advancements and future research challenges in predicting network topology.

Keywords:
Computer scienceNetworkNetwork topology

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Area of Science:

  • Network Science
  • Data Mining
  • Computer Science

Background:

  • Link prediction is crucial for understanding network structures.
  • Estimating non-observed links is vital in various network science applications.
  • Existing methods require comprehensive review to guide future research.

Purpose of the Study:

  • To provide a comprehensive review of link prediction techniques.
  • To summarize recent advancements in the field over the last decade.
  • To identify and discuss challenges for future link prediction research.

Main Methods:

  • Review of local similarity indices.
  • Analysis of network embedding techniques.
  • Exploration of matrix completion and ensemble learning methods.

Main Results:

  • Summarized representative progress in link prediction methodologies.
  • Detailed various approaches including local similarity, network embedding, and matrix completion.
  • Highlighted key challenges and future research directions.

Conclusions:

  • Link prediction is a dynamic field with continuous advancements.
  • Network embedding and matrix completion show significant promise.
  • Further research is needed to address existing challenges in link prediction.