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Automatic Annotation of a Dynamic Corpus by Label Propagation

  • Thomas Lansdall-Welfare
  • Ilias Flaounas
  • Nello Cristianini
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 30)

Abstract

We are interested in the problem of automatically annotating a large, constantly expanding corpus, in the case where potentially neither the dataset nor the class of possible labels that can be used are static, and the annotation of the data needs to be efficient. This application is motivated by real-world scenarios of news content analysis and social-web content analysis. We investigate a method based on the creation of a graph, whose vertices are the documents and the edges represent some notion of semantic similarity. In this graph, label propagation algorithms can be efficiently used to apply labels to documents based on the annotation of their neighbours. This paper presents experimental results about both the efficient creation of the graph and the propagation of the labels. We compare the effectiveness of various approaches to graph construction by building graphs of 800,000 vertices based on the Reuters corpus, showing that relation-based classification is competitive with support vector machines, which can be considered as state of the art. We also show that the combination of our relation-based approach and support vector machines leads to an improvement over the methods individually.

Keywords

Graph construction Label propagation Large scale Text categorisation 

Notes

Acknowledgements

I. Flaounas and N. Cristianini are supported by FP7 under grant agreement no. 231495 (ComPLACS Project). N. Cristianini is supported by Royal Society Wolfson Research Merit Award. All authors are supported by Pascal2 Network of Excellence.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Thomas Lansdall-Welfare
    • 1
  • Ilias Flaounas
    • 1
  • Nello Cristianini
    • 1
  1. 1.Intelligent Systems LaboratoryUniversity of BristolBristolUK

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