Did I Miss Anything? A Study on Ranking Fusion and Manual Query Rewriting in Consumer Health Search

In this paper, we describe the methodology and experimental analysis of a twofold strategy for the retrieval of medical relevant information: a ranking fusion and a query reformulation approach. In particular, the query reformulation approach is based on the idea that a query is composed of two parts: the primary term and the secondary term of the query, and that these two parts can be substituted with alternative terms to create a reformulation of the original query. The goal of our work is to evaluate the performances of a search engine over 1) manual query variants; 2) different retrieval functions; 3) w/out pseudo-relevance feedback; 4) reciprocal ranking fusion. We describe the experiments based on the CLEF eHealth 2021 Consumer Health Search Task dataset. The results show that 1) a ranking fusion approach of the baseline models improves MAP significantly; 2) manual query variants open new questions about possible an unintentional bias in the pool of documents that were selected for relevance assessment.