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Tagging Scientific Publications Using Wikipedia and Natural Language Processing Tools

Comparison on the ArXiv Dataset
  • Michał Łopuszyński
  • Łukasz Bolikowski
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 416)

Abstract

In this work, we compare two simple methods of tagging scientific publications with labels reflecting their content. As a first source of labels Wikipedia is employed, second label set is constructed from the noun phrases occurring in the analyzed corpus. We examine the statistical properties and the effectiveness of both approaches on the dataset consisting of abstracts from 0.7 million of scientific documents deposited in the ArXiv preprint collection. We believe that obtained tags can be later on applied as useful document features in various machine learning tasks (document similarity, clustering, topic modelling, etc.).

Keywords

Tagging document collections Natural language processing Wikipedia 

Notes

Acknowledgement

This research was carried out with the support of the “HPC Infrastructure for Grand Challenges of Science and Engineering (POWIEW)” Project, co-financed by the European Regional Development Fund under the Innovative Economy Operational Programme.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Interdisciplinary Centre for Mathematical and Computational ModellingUniversity of WarsawWarsawPoland

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