Effective query expansion with the resistance distance based term similarity metric

In this paper, we define a new query expansion method that relies on term similarity metric derived from the electric resistance network. This proposed metric lets us measure the mutual relevancy in between terms and between their groups. This paper shows how to define this metric automatically from the document collection, and then apply it in query expansion for document retrieval tasks. The experiments show this method can be used to find good expansion terms of search queries and improve document retrieval performance on two TREC genomic track datasets.