Keyphrases Extraction from Scientific Documents: Improving Machine Learning Approaches with Natural Language Processing

@inproceedings{Krapivin2010KeyphrasesEF,
  title={Keyphrases Extraction from Scientific Documents: Improving Machine Learning Approaches with Natural Language Processing},
  author={Mikalai Krapivin and Aliaksandr Autayeu and Maurizio Marchese and Enrico Blanzieri and Nicola Segata},
  booktitle={ICADL},
  year={2010}
}
In this paper we use Natural Language Processing techniques to improve different machine learning approaches (Support Vector Machines (SVM), Local SVM, Random Forests) to the problem of automatic keyphrases extraction from scientific papers. For the evaluation we propose a large and high-quality dataset: 2000 ACM papers from the Computer Science domain. We evaluate by comparison with expert-assigned keyphrases. Evaluation shows promising results that outperform state-of-the-art Bayesian… CONTINUE READING

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