Automatic Classification of Swedish Metadata Using Dewey Decimal Classification: A Comparison of Approaches

Automatic Classification of Swedish Metadata Using Dewey Decimal Classification: A Comparison of Approaches

With more and more digital collections of various information resources becoming available, also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization systems. While the ultimate purpose is to understand the value of automatically produced Dewey...

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Bibliographic Details
Main Authors: Golub Koraljka, Hagelbäck Johan, Ardö Anders
Format: Article
Language:English
Published: Sciendo 2020-04-01
Series:Journal of Data and Information Science
Subjects:
libris
dewey decimal classification
automatic classification
machine learning
support vector machine
multinomial naïve bayes
simple linear network
standard neural network
1d convolutional neural network
recurrent neural network
word embeddings
string matching
Online Access:https://doi.org/10.2478/jdis-2020-0003
Description
Summary:With more and more digital collections of various information resources becoming available, also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization systems. While the ultimate purpose is to understand the value of automatically produced Dewey Decimal Classification (DDC) classes for Swedish digital collections, the paper aims to evaluate the performance of six machine learning algorithms as well as a string-matching algorithm based on characteristics of DDC.
ISSN:2543-683X

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