Joint learning of author and citation contexts for computing drift in scholarly documents

Scholarly documents are sources of information on research topics written by academic experts. Topic drift in such scholarly documents is usually linked with the contextual variation in the title or abstract or entire document over time. However, topic distribution over words in different components...

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Vydané v:	International journal of machine learning and cybernetics Ročník 12; číslo 6; s. 1667 - 1686
Hlavní autori:	Vijayarani, J., Geetha, T. V.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2021 Springer Nature B.V
Predmet:	Artificial Intelligence Bivariate analysis Brownian motion Citation analysis Citations Complex Systems Computational Intelligence Context Control Documents Drift Engineering Influence Keywords Mechatronics Original Article Pattern Recognition Robotics Semantics Systems Biology Trends Brownian motion Topic drift Topical word embedding Joint learning Context vector Weighted citation
ISSN:	1868-8071, 1868-808X
On-line prístup:	Získať plný text
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