4 research outputs found
Efficient Parameter Estimation for Information Retrieval Using Black-Box Optimization
open4openCosta A.; Di Buccio E.; Melucci M.; Nannicini G.Costa, A.; Di Buccio, E.; Melucci, M.; Nannicini, G
What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way
From 2017 to 2019 the Text REtrieval Conference (TREC) held a challenge task
on precision medicine using documents from medical publications (PubMed) and
clinical trials. Despite lots of performance measurements carried out in these
evaluation campaigns, the scientific community is still pretty unsure about the
impact individual system features and their weights have on the overall system
performance. In order to overcome this explanatory gap, we first determined
optimal feature configurations using the Sequential Model-based Algorithm
Configuration (SMAC) program and applied its output to a BM25-based search
engine. We then ran an ablation study to systematically assess the individual
contributions of relevant system features: BM25 parameters, query type and
weighting schema, query expansion, stop word filtering, and keyword boosting.
For evaluation, we employed the gold standard data from the three TREC-PM
installments to evaluate the effectiveness of different features using the
commonly shared infNDCG metric.Comment: Accepted for SIGIR2020, 10 page