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Towards Content Expiry Date Determination: Predicting Validity Periods of Sentences

  • Axel Almquist
  • Adam JatowtEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11437)

Abstract

Knowing how long text content will remain valid can be useful in many cases such as supporting the creation of documents to prolong their usefulness, improving document retrieval or enhancing credibility estimation. In this paper we introduce a novel research task of forecasting content’s validity period. Given an input sentence the task is to approximately determine until when the information stated in the content will remain valid. We propose machine learning approaches equipped with NLP and statistical features that can successfully work on a relatively small number of annotated data.

Keywords

Content validity scope estimation Text classification Natural language processing Machine learning 

Notes

Acknowledgements

We thank Nina Tahmasebi for valuable comments and encouragement. This research has been supported by JSPS KAKENHI Grants (#17H01828, #18K19841) and by Microsoft Research Asia 2018 Collaborative Research Grant.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.SentiSumLondonUK
  2. 2.Kyoto UniversityKyotoJapan

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