Generating synopses for document-element search
Proceedings of the 18th ACM conference on Information and knowledge management
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Finding algorithms in scientific articles
Proceedings of the 19th international conference on World wide web
An algorithm search engine for software developers
Proceedings of the 3rd International Workshop on Search-Driven Development: Users, Infrastructure, Tools, and Evaluation
Summarizing figures, tables, and algorithms in scientific publications to augment search results
ACM Transactions on Information Systems (TOIS)
A classification scheme for algorithm citation function in scholarly works
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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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.