Work

Search Efficiency for Score-at-a-Time Retrieval

Year: 2025

Type: conference-paper

Abstract: Impact-ordered indexes, and thus Score-at-a-Time (SaaT) retrieval, is seeing a resurgence due to the emergence of learned sparse representations [4] (LSR) which employ the use of neural networks to learn the term-document weights. Within this context, SaaT has been found to be a competitive alternative to the more studied Document-at-a-Time (DaaT) approach.

Source: International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

DOI: 10.1145/3726302.3730123

Author: Katelyn Harlan

Institution: University of Otago

Language: English

Topic: Information Retrieval and Search Behavior

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4412378243

FWCI:

Cites: 6

Cited by:

Related to: 10