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Measuring Global Similarity between Texts

Abstract : We propose a new similarity measure between texts which, contrary to the current state-of-the-art approaches, takes a global view of the texts to be compared. We have implemented a tool to compute our textual distance and conducted experiments on several corpuses of texts. The experiments show that our methods can reliably identify different global types of texts.
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Submitted on : Tuesday, November 25, 2014 - 4:36:56 PM
Last modification on : Thursday, January 20, 2022 - 5:33:20 PM
Long-term archiving on: : Thursday, February 26, 2015 - 12:10:56 PM


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Uli Fahrenberg, Fabrizio Biondi, Kevin Corre, Cyrille Jegourel, Simon Kongshøj, et al.. Measuring Global Similarity between Texts. SLSP 2014 : Second International Conference on Statistical Language and Speech Processing, Oct 2014, Grenoble, France. pp.220-232, ⟨10.1007/978-3-319-11397-5_17⟩. ⟨hal-01087009⟩



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