An information-theoretic perspective of tf–idf measures
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Some retrieval metrics, such as recall, precision, and F1 score, are order-unaware and do not take into consideration the order of the retrieved results set.
“Some of these are order-unaware metrics (like recall, precision, F1 score, etc.) and do not take into consideration the order of the retrieved results set 35,36 .”
From Automated Knowledge Organization AI ML based Subject Indexing System for Libraries (2023) · cites this paper as [35]
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Automated Knowledge Organization AI ML based Subject Indexing System for Libraries
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MR-MAS: an end-to-end multi-agent system for autonomous Mendelian randomization analysis
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“It then combines keyword-based recall with semantic ranking based on TF-IDF similarity (Aizawa 2003) to identify the most relevant trait candidates.”
- Authors
- Aizawa, A.
- Affiliations
- National Institute of Informatics (JP)
- Corresponding author
- Aizawa, Akiko
- ORCID
- Aizawa, Akiko
- Venue
- Information Processing & Management
- Publisher
- Elsevier BV
- Published
- 2003-01
- Volume
- 39
- Issue
- 1
- Pages
- 45-65
- ISSN
- 0020-0271 (ISSN-L)
- 0306-4573
- OpenAlex
- W2101746535
- Cited by
- 1,419
- References
- 0
- Citations by year
- 2026: 73 · 2025: 161 · 2024: 170 · 2023: 178 · 2022: 151 · 2021: 135 · 2020: 97 · 2019: 87 · 2018: 62 · 2017: 44 · 2016: 47 · 2015: 45 · 2014: 33 · 2013: 24 · 2012: 21
- FWCI
- 9.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Processing & Management (publishedVersion)
- Funders
- National Institute of Informatics
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Text Analysis Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Keywords
- TF-IDF, term specificity
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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