Improving algorithm search using the algorithm co-citation network

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.