Temporal Concept Drift and Alignment: An empirical approach to comparing Knowledge Organization Systems over time

TL;DR

This paper investigates how knowledge organization systems change over time by analyzing historical and modern vocabularies, demonstrating that historical vocabularies can reveal conceptual drift and improve contextual understanding of historical resources.

Contribution

It introduces a methodology for studying temporal concept drift in KOS using historical and contemporary vocabularies and NLP techniques.

Findings

Historical vocabularies reveal conceptual drift over time.

Deprecated terms in modern vocabularies reflect historical language.

Methodology improves contextualization of historical resources.

Abstract

This research explores temporal concept drift and temporal alignment in knowledge organization systems (KOS). A comparative analysis is pursued using the 1910 Library of Congress Subject Headings, 2020 FAST Topical, and automatic indexing. The use case involves a sample of 90 nineteenth-century Encyclopedia Britannica entries. The entries were indexed using two approaches: 1) full-text indexing; 2) Named Entity Recognition was performed upon the entries with Stanza, Stanford's NLP toolkit, and entities were automatically indexed with the Helping Interdisciplinary Vocabulary application (HIVE), using both 1910 LCSH and FAST Topical. The analysis focused on three goals: 1) identifying results that were exclusive to the 1910 LCSH output; 2) identifying terms in the exclusive set that have been deprecated from the contemporary LCSH, demonstrating temporal concept drift; and 3) exploring the historical significance of these deprecated terms. Results confirm that historical vocabularies can be used to generate anachronistic subject headings representing conceptual drift across time in KOS and historical resources. A methodological contribution is made demonstrating how to study changes in KOS over time and improve the contextualization of historical humanities resources.