The Hybrid Method for Accurate Patent Classification
- Авторлар: Yadrintsev V.1,2, Sochenkov I.1,3
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Мекемелер:
- Federal Research Center Computer Science and Control of the Russian Academy of Sciences
- Peoples’ Friendship University of Russia (RUDN University)
- Lomonosov Moscow State University
- Шығарылым: Том 40, № 11 (2019)
- Беттер: 1873-1880
- Бөлім: Article
- URL: https://journals.rcsi.science/1995-0802/article/view/206101
- DOI: https://doi.org/10.1134/S1995080219110325
- ID: 206101
Дәйексөз келтіру
Аннотация
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.
Негізгі сөздер
Авторлар туралы
V. Yadrintsev
Federal Research Center Computer Science and Control of the Russian Academy of Sciences; Peoples’ Friendship University of Russia (RUDN University)
Хат алмасуға жауапты Автор.
Email: vvyadrincev@gmail.com
Ресей, Moscow, 119333; Moscow, 117198
I. Sochenkov
Federal Research Center Computer Science and Control of the Russian Academy of Sciences; Lomonosov Moscow State University
Хат алмасуға жауапты Автор.
Email: sochenkov@isa.ru
Ресей, Moscow, 119333; Moscow, 119991