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Unsupervised Keyword Extraction Using the GoW Model and Centrality Scores

  • Elissavet Batziou
  • Ilias GialampoukidisEmail author
  • Stefanos Vrochidis
  • Ioannis Antoniou
  • Ioannis Kompatsiaris
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10673)

Abstract

Nowadays, a large amount of text documents are produced on a daily basis, so we need efficient and effective access to their content. News articles, blogs and technical reports are often lengthy, so the reader needs a quick overview of the underlying content. To that end we present graph-based models for keyword extraction, in order to compare the Bag of Words model with the Graph of Words model in the keyword extraction problem. We compare their performance in two publicly available datasets using the evaluation measures Precision@10, mean Average Precision and Jaccard coefficient. The methods we have selected for comparison are grouped into two main categories. On the one hand, centrality measures on the formulated Graph-of-Words (GoW) are able to rank all words in a document from the most central to the less central, according to their score in the GoW representation. On the other hand, community detection algorithms on the GoW provide the largest community that contains the key nodes (words) in the GoW. We selected these methods as the most prominent methods to identify central nodes in a GoW model. We conclude that term-frequency scores (BoW model) are useful only in the case of less structured text, while in more structured text documents, the order of words plays a key role and graph-based models are superior to the term-frequency scores per document.

Keywords

Keyword-based search Topic-based filtering Graph-based models Graph of words Centrality measures Community detection 

Notes

Acknowledgements

This work was supported by the projects H2020-645012 (KRISTINA) and H2020-700024 (TENSOR), funded by the European Commission.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Elissavet Batziou
    • 1
  • Ilias Gialampoukidis
    • 2
    Email author
  • Stefanos Vrochidis
    • 2
  • Ioannis Antoniou
    • 1
  • Ioannis Kompatsiaris
    • 2
  1. 1.School of MathematicsAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Centre for Research and Technology Hellas, Information Technologies InstituteThessalonikiGreece

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