The Hybrid Method for Accurate Patent Classification


Ядринцев В. В. Соченков И. В.


This article is dedicated to stacking of two approaches of patent classification. First is based on linguistically-supported k-nearest neighbors algorithm using the method of search for topically similar documents based on a comparison of vectors of lexical descriptors. Second is the word embeddings based fastText, where the sentence (or a document) vector is obtained by averaging the n-gram embeddings, and then a multinomial logistic regression exploits these vectors as features. We show in Russian and English datasets that stacking classifier shows better results compared to single classifiers.

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Yadrintsev V. V., Sochenkov I. V. The Hybrid Method for Accurate Patent Classification // Lobachevskii Journal of Mathematics, 2019, Volume 40, Issue 11, pp 1873–1880.