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arXiv:cs/0312018cs.IR

Mapping Subsets of Scholarly Information

Paul Ginsparg, Paul Houle, Thorsten Joachims, Jae-Hoon Sul

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Abstract

We illustrate the use of machine learning techniques to analyze, structure, maintain, and evolve a large online corpus of academic literature. An emerging field of research can be identified as part of an existing corpus, permitting the implementation of a more coherent community structure for its practitioners.

arXiv comments
10 pages, 4 figures, presented at Arthur M. Sackler Colloquium on "Mapping Knowledge Domains", 9--11 May 2003, Beckman Center, Irvine, CA, proceedings to appear in PNAS
Journal reference
DOI
doi:10.1073/pnas.0308253100
Subjects
cs.IRInformation Retrieval cs.LGMachine Learning

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Linked by 1 identifiable commenter in 2 comments across 2 threads, from Apr 2023 to Nov 2024.

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Discussed in comments2 threads

  1. To what extent is science a strong-link problem? 1 comment

    • A long time ago I got a paper with my name on it in PNAS because a professor I knew had been invited to submit one as part of a conference (bypassing the usual peer review) so I got together with another prof and a student and we smashed together a few student research projects…

      PaulHouleView on HNParent context

  2. Ask HN: Most interesting tech you built for just yourself? 1 comment

    • Smart RSS reader that, right now, ingests about 1000 articles a day and picks out 300 for me to skim. Since I helped write this paper https://arxiv.org/abs/cs/0312018 I was always asking "Why is RSS failing? Why do failing RSS readers keep using the same failing interface that…

      PaulHouleView on HNParent context

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