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Master Thesis Year : 2020

Extracting scientific results from research articles


The basic unit of information of use by researchers in theoretical fields are the mathematical results. We aim to build a knowledge base of these results, using information extraction techniques on scholarly documents. We present an algorithm which extracts mathematical results and references to mathematical results from scientific papers, using their PDF or LATEX sources. We analyse the results of our algorithm on the whole arXiv database of scientific papers and explore the resulting graph of mathematical results, which contains more than 6 million results and 4.5 million edges. We present attempts to link theorems of different papers using a TFIDF vectorizer or an autoencoder.
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hal-02956526 , version 1 (02-10-2020)


  • HAL Id : hal-02956526 , version 1


Lucas Pluvinage. Extracting scientific results from research articles. Artificial Intelligence [cs.AI]. 2020. ⟨hal-02956526⟩
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