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

Abstract

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.

Keywords

• 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