Using wavelet analysis for text categorization in digital libraries a first experiment with Strathprints

• Published in: International journal on digital libraries
• Main Authors: Darányi, Sándor, Wittek, Peter, Dobreva, Milena
• Format: Journal Article
• Language: English
• Published: 2011
• Subjects: analogical information representation; Biblioteks- och informationsvetenskap; digital libraries; hilbert spaces; kernel methods; Library and Information Science; machine learning; semantic enrichment; support vector machines; text categorization; text classification; wavelet analysis
• ISSN: 1432-1300; 1432-5012

Digital libraries increasingly bene t from re- search on automated text categorization for improved access. Such research is typically carried out by using standard test collections. In this paper we present a pilot experiment of replacing such test collections by a set of 6000 objects from a real-world digital repos- itory, indexed by Library of Congress Subject Head- ings, and test support vector machines in a supervised learning setting for their ability to reproduce the exist- ing classi cation. To augment the standard approach, we introduce a combination of two novel elements: us- ing functions for document content representation in Hilbert space, and adding extra semantics from lexical resources to the representation. Results suggest that wavelet-based kernels slightly outperformed traditional kernels on classi cation reconstruction from abstracts and vice versa from full-text documents, the latter out- come due to word sense ambiguity. The practical imple- mentation of our methodological framework enhances the analysis and representation of speci c knowledge relevant to large-scale digital collections, in this case the thematic coverage of the collections. Representation of speci c knowledge about digital collections is one of the basic elements of the persistent archives and the less studied one (compared to representations of digital ob- jects and collections). Our research is an initial step in this direction developing further the methodological ap- proach and demonstrating that text categorisation can be applied to analyse the thematic coverage in digital repositories.