Cited by 570Text and Document Classification TechnologiesAdvanced Text Analysis TechniquesInformation Retrieval and Search Behavior

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Automatic Indexing: An Experimental Inquiry

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Maron, M. E.·1961·Journal of the ACM

DOI 10.1145/321075.321084

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Abstract

This inquiry examines a technique for automatically classifying (indexing) documents according to their subject content.The task, in essence, is to have a computing machine read a document and on the basis of the occurrence of selected clue words decide to which of many subject categories the document in question belongs.This paper describes the design, execution and evaluation of a modest experimental study aimed at testing empirically one statistical technique for automatic indexing.

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On Relevance, Probabilistic Indexing and Information Retrieval
Maron, M. E., & Kuhns, J. L. (1960) · Journal of the ACM · doi:10.1145/321033.321035 · Cited by 908
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1. Engines of Order
Rieder, B. (2020) · Amsterdam University Press eBooks · doi:10.1515/9789048537419-003
“In the paper that first laid out what is now known as a Bayes classifier (Chapter 6), M. E. Maron (1961) programmatically states ‘that statistics on kind, frequency, location, order, etc., of selected words are adequate to make reasonably good predictions about the subject matter of documents…”
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“Naive Bayesian Classifier Naive Bayesian classifier (Maron, 1961) is based on probabilistic inference 232 of samples observed where the decision variable and the features form a very naive structure of Bayesian 233 Network.”
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Method
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Mi, L., Yuan, J., Zhou, Y., & Hou, X. (2025) · Journal of Shanghai Jiaotong University (Science) · doi:10.1007/s12204-025-2825-5
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Authors: Maron, M. E.
Affiliations: RAND Corporation (US)
Corresponding author: Maron, M. E.
Venue: Journal of the ACM
Publisher: Association for Computing Machinery (ACM)
Published: 1961-07
Volume: 8
Issue: 3
Pages: 404-417
ISSN: 0004-5411 (ISSN-L)
1557-735X
DOI: 10.1145/321075.321084
OpenAlex: W2009190245
Cited by: 570
References: 1
Citations by year: 2026: 18 · 2025: 16 · 2024: 22 · 2023: 27 · 2022: 29 · 2021: 57 · 2020: 82 · 2019: 44 · 2018: 14 · 2017: 11 · 2016: 9 · 2015: 12 · 2014: 7 · 2013: 10 · 2012: 22
FWCI: 9.89
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations: Journal of the ACM (publishedVersion)
Defense Technical Information Center (DTIC) (submittedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
Physical Sciences › Computer Science › Artificial Intelligence › Advanced Text Analysis Techniques
Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
Keywords: automatic indexing, document classification, subject classification, clue words, statistical classification, subject categories, information retrieval

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Automatic Indexing: An Experimental Inquiry

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