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  5. AN EVOLUTIONARY APPROACH TO BIBLIOGRAPHIC CLASSIFICATION
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AN EVOLUTIONARY APPROACH TO BIBLIOGRAPHIC CLASSIFICATION

Date Issued
August 11, 2018
Author(s)
Sims, David Linn
Advisor(s)
Suzanne L. Allard
Additional Advisor(s)
David G. Anderson
Bradley Wade Bishop
Stuart N. Brotman
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/26289
Abstract

This dissertation is research in the domain of information science and specifically, the organization and representation of information. The research has implications for classification of scientific books, especially as dissemination of information becomes more rapid and science becomes more diverse due to increases in multi-, inter-, trans-disciplinary research, which focus on phenomena, in contrast to traditional library classification schemes based on disciplines.The literature review indicates 1) human socio-cultural groups have many of the same properties as biological species, 2) output from human socio-cultural groups can be and has been the subject of evolutionary relationship analyses (i.e., phylogenetics), 3) library and information science theorists believe the most favorable and scientific classification for information packages is one based on common origin, but 4) library and information science classification researchers have not demonstrated a book classification based on evolutionary relationships of common origin.The research project supports the assertion that a sensible book classification method can be developed using a contemporary biological classification approach based on common origin, which has not been applied to a collection of books until now. Using a sample from a collection of earth-science digitized books, the method developed includes a text-mining step to extract important terms, which were converted into a dataset for input into the second step—the phylogenetic analysis. Three classification trees were produced and are discussed. Parsimony analysis, in contrast to distance and likelihood analyses, produced a sensible book classification tree. Also included is a comparison with a classification tree based on a well-known contemporary library classification scheme (the Library of Congress Classification).Final discussions connect this research with knowledge organization and information retrieval, information needs beyond science, and this type of research in context of a unified science of cultural evolution.

Degree
Doctor of Philosophy
Major
Communication and Information
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utk.ir.td_545.pdf

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