A selective approach to stemming for minimizing the risk of failure in information retrieval systems.

ABSTRACT: Stemming is supposed to improve the average performance of an information retrieval system, but in practice, past experimental results show that this is not always the case. In this article, we propose a selective approach to stemming that decides whether stemming should be applied or not on a query basis. Our method aims at minimizing the risk of failure caused by stemming in retrieving semantically-related documents. The proposed work mainly contributes to the IR literature by proposing an application of selective stemming and a set of new features that derived from the term frequency distributions of the systems in selection. The method based on the approach leverages both some of the query performance predictors and the derived features and a machine learning technique. It is comprehen

SUBMITTER: Goksel G 

PROVIDER: S-EPMC10280253 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature