Skip to main navigation Skip to search Skip to main content

Improving algorithm search using the algorithm co-citation network

  • Suppawong Tuarob
  • , Prasenjit Mitra
  • , C. Lee Giles

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Algorithms are an essential part of computational science. An algorithm search engine, which extracts pseudo-codes and their metadata from documents, and makes it searchable, has recently been developed as part of the CiteseerX suite. However, this algorithm search engine only retrieves and ranks relevant algorithms solely on textual similarity. Here, we propose a method for using the algorithm co-citation network to infer the similarity between algorithms. We apply a graph clustering algorithm on the network for algorithm recommendation and make suggestions on how to improve the current CiteseerX algorithm search engine.

Original languageEnglish (US)
Title of host publicationJCDL 2012 - Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages277-280
Number of pages4
ISBN (Print)9781450311540
DOIs
StatePublished - 2012
Event12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2012 - Washington, DC, United States
Duration: Jun 10 2012 → Jun 14 2012

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN (Print)1552-5996

Conference

Conference12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2012
Country/TerritoryUnited States
CityWashington, DC
Period6/10/12 → 6/14/12

All Science Journal Classification (ASJC) codes

  • General Engineering

Fingerprint

Dive into the research topics of 'Improving algorithm search using the algorithm co-citation network'. Together they form a unique fingerprint.

Cite this