DeepStyle: User style embedding for authorship attribution of short texts

• Main Authors: HU, Zhiqiang, LEE, Roy Ka-Wei, WANG, Lei, LIM, Ee-Peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Authorship attribution; Style embedding; Triplet loss; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/6018; https://ink.library.smu.edu.sg/context/sis_research/article/7021/viewcontent/DeepStyleUserStyleEmbedding_av_2020.pdf; https://ink.library.smu.edu.sg/context/sis_research/article/7021/filename/0/type/additional/viewcontent/505687_1_En_17_MOESM1_ESM.pdf
• Institution: Singapore Management University

Authorship attribution (AA), which is the task of finding the owner of a given text, is an important and widely studied research topic with many applications. Recent works have shown that deep learning methods could achieve significant accuracy improvement for the AA task. Nevertheless, most of thes...