Skip to main content

Mapping Knowledge Domains (2004) / Chapter Skim
Currently Skimming:

INTRODUCTION: Mapping knowledge domains
Pages 1-3

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 1...
... Achieving such results requires tools from diverse areas of science: ways to analyze truly enormous amounts of data and extract meaningful results; ways to sort and cluster information This paper serves as an introduction to the following papers, which result from the Arthur M Sackier Colioquium of the National Academy of Sciences, "Mapping Knowledge Domains," held May 9-11, 2003, at the Arnold and Mabel Beckman Center of the National Academies of Sciences and Engineering in Irvine, CA.
Read the entire page →
From page 2...
... and of the content of the papers and web pages, thereby reproducing network "degree" and content similarity distributions. Katy Borner, Jeegar Maru, and Robert Goldstone present a simple process model that simultaneously grows coauthor and paper-citation networks; the statistical and dynamic properties of the simulated network data are validated against a 20-year PNAS data set.
Read the entire page →
From page 3...
... Sullenberger, executive editor, PNAS. The 20-year PNAS citation data set was extracted from Science Citation Index Expanded "Institute for Scientific Information, Inc.
Read the entire page →

Key Terms

  • pnas database
  • knowledge domains
  • chaomei chen
  • beckman center
  • ketan mane

  • sackler colloquium
  • jon kleinberg
  • common format
  • coauthor networks
  • articles address

  • katy borner
  • sandia national
  • information science
  • kevin boyack
  • mabel beckman

  • dynamic changes
  • paul houle
  • highlight economic
  • classify research
  • correlate highly

  • filippo menczer
  • rapidly generates
  • identify real
  • future day
  • simple process

  • pathfinder networks
  • individual researchers
  • following papers
  • author collaboration
  • underlying algorithms


    • This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
    More information on Chapter Skim is available.