Working Paper Article Version 1 This version is not peer-reviewed

A Study of a Gain Based Approach for Query Aspects in Recall Oriented Tasks

Version 1 : Received: 12 September 2021 / Approved: 13 September 2021 / Online: 13 September 2021 (09:56:16 CEST)

A peer-reviewed article of this Preprint also exists.

Di Nunzio, G.M.; Faggioli, G. A Study of a Gain Based Approach for Query Aspects in Recall Oriented Tasks. Appl. Sci. 2021, 11, 9075. Di Nunzio, G.M.; Faggioli, G. A Study of a Gain Based Approach for Query Aspects in Recall Oriented Tasks. Appl. Sci. 2021, 11, 9075.

Journal reference: Appl. Sci. 2021, 11, 9075
DOI: 10.3390/app11199075

Abstract

Evidence-based healthcare integrates the best research evidence with clinical expertise in order to make decisions based on the best practices available. In this context, the task of collecting all the relevant information, a recall oriented task, in order to take the right decision within a reasonable time frame has become an important issue. In this paper, we investigate the problem of building an effective Consumer Health Search (CHS) systems that use query variations to achieve high recall and fulfill the information needs of health consumers. In particular, we study an intent-aware gain metric used to estimate the amount of missing information and make a prediction about the achievable recall for each query reformulation during a search session. We evaluate and propose alternative formulations of this metric using standard test collections of the CLEF 2018 eHealth Evaluation Lab CHS.

Keywords

Query Variations; Query Reformulations; Query Performance Prediction; Systematic Reviews

Subject

MATHEMATICS & COMPUTER SCIENCE, Information Technology & Data Management

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