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2019 | OriginalPaper | Chapter

Semantically Aware Text Categorisation for Metadata Annotation

Authors : Giulio Carducci, Marco Leontino, Daniele P. Radicioni, Guido Bonino, Enrico Pasini, Paolo Tripodi

Published in: Digital Libraries: Supporting Open Science

Publisher: Springer International Publishing

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Abstract

In this paper we illustrate a system aimed at solving a long-standing and challenging problem: acquiring a classifier to automatically annotate bibliographic records by starting from a huge set of unbalanced and unlabelled data. We illustrate the main features of the dataset, the learning algorithm adopted, and how it was used to discriminate philosophical documents from documents of other disciplines. One strength of our approach lies in the novel combination of a standard learning approach with a semantic one: the results of the acquired classifier are improved by accessing a semantic network containing conceptual information. We illustrate the experimentation by describing the construction rationale of training and test set, we report and discuss the obtained results and conclude by drawing future work.

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https://ethos.bl.uk.

http://ethostoolkit.cranfield.ac.uk.

Full account of the EThOS UKETD_DC application profile can be found at the URL http://ethostoolkit.cranfield.ac.uk/tiki-index.php?page=Metadata.

The final test set is available within the bundle containing the implementation of the described system [4].

An off-the shelf implementation of the Random Forest algorithm was used, as provided by the scikit-learn framework, http://scikit-learn.org/stable/.

We used the list of English stop-words from the NLTK package available at the URL https://gist.github.com/sebleier/554280.

Stemming was done using the WordNet Lemmatizer, also available within the NLTK library, https://github.com/nltk/nltk/blob/develop/nltk/stem/wordnet.py.

It is worth noting that the human experts adopted a rather inclusive attitude with respect to religious studies, based on their previous acquaintance with an analogous dataset of US PhD dissertations, in which a significant number of ‘religious’ dissertations have been defended in philosophy departments.

We obtained a list of some relevant philosophical concepts from the upper levels of the Taxonomy of Philosophy by David Chalmers, http://consc.net/taxonomy.html.

We presently employ the Stanford Named Entity Recognizer [10].

We presently employ the Stanford POS Tagger [31].

The implemented system is delivered through the Zenodo platform [4].

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Title: Semantically Aware Text Categorisation for Metadata Annotation
Authors: Giulio Carducci
Marco Leontino
Daniele P. Radicioni
Guido Bonino
Enrico Pasini
Paolo Tripodi
Publisher: Springer International Publishing
Book: Digital Libraries: Supporting Open Science
Print ISBN: 978-3-030-11225-7

Electronic ISBN: 978-3-030-11226-4

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-11226-4_25