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U.S. Department of Energy
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Workshop on Incomplete Network Data Held at Sandia National Labs – Livermore

Technical Report ·
DOI:https://doi.org/10.2172/1259543· OSTI ID:1259543
 [1];  [2]
  1. Syracuse Univ., NY (United States)
  2. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
While network analysis is applied in a broad variety of scientific fields (including physics, computer science, biology, and the social sciences), how networks are constructed and the resulting bias and incompleteness have drawn more limited attention. For example, in biology, gene networks are typically developed via experiment -- many actual interactions are likely yet to be discovered. In addition to this incompleteness, the data-collection processes can introduce significant bias into the observed network datasets. For instance, if you observe part of the World Wide Web network through a classic random walk, then high degree nodes are more likely to be found than if you had selected nodes at random. Unfortunately, such incomplete and biasing data collection methods must be often used.
Research Organization:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1259543
Report Number(s):
SAND2016--5324R; 641383
Country of Publication:
United States
Language:
English

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