Search Efficiency for Score-at-a-Time Retrieval

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.

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Published
2025-07-13
DOI
https://doi.org/10.1145/3726302.3730123
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
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article

Search Efficiency for Score-at-a-Time Retrieval

Katelyn Harlan
Algorithms and Data Compression
article

Search Efficiency for Score-at-a-Time Retrieval

Katelyn Harlan
article en

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.

University of Otago (NZ)
Openalex Percentile: Top 92%
Algorithms and Data Compression
DOIOpen Access PDFOpenAlex
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Search Efficiency for Score-at-a-Time Retrieval — Katelyn Harlan · (2025) | TGRS Research Map | TGRS