Inferring the hierarchical structure of citation networks to improve semantic search of the scholarly literature
2014 - 2016
In past studies we have found it possible to build a powerful recommendation engine based upon the hierarchical structure of the scholarly literature, as extracted using our InfoMap network clustering algorithm. Here we propose to extend this approach to build methods for semantic search that take the structure of the scholarly literature into account, guiding researchers to important documents within knowledge communities to which their query terms are of greatest relevance. By combining hierarchical citation analysis with text-based searching, we aim to provide new tools for scholarly navigation.