Improving algorithm search using the algorithm co-citation network

Suppawong Tuarob, Prasenjit Mitra, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

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 '12 - Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries
Pages277-280
Number of pages4
DOIs
StatePublished - 2012
Event12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12 - Washington, DC, United States
Duration: Jun 10 2012Jun 14 2012

Publication series

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

Other

Other12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12
CountryUnited States
CityWashington, DC
Period6/10/126/14/12

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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