Quantum-inspired density matrix encoder for sexual harassment personal stories classification

Peng Yan, Linjing Li, Weiyun Chen, Daniel Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays, more and more sexual harassment personal stories have been shared on social media. To better monitor and analyze the extent of sexual harassment based on these social media data, we need to automatically categorize different forms of sexual harassment personal stories. Existing methods apply convolutional neural network (CNN) with different convolution window sizes to this text classification task. However, the previous CNN models do not provide an effective way to synthesize window size-related local representations, but simply concatenate all local representations together. To address this problem, we propose a new density matrix encoder, inspired by quantum mechanics, to encode local representations as particles in quantum state and generate a global representation as quantum mixed system for each story. Experiment on SafeCity dataset shows that our model outperforms CNN baseline and achieves better performance than the state-of-the-art model when considering both accuracy and speed, demonstrating the effectiveness of the proposed density matrix encoder.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019
EditorsXiaolong Zheng, Ahmed Abbasi, Michael Chau, Alan Wang, Lina Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages218-220
Number of pages3
ISBN (Electronic)9781728125046
DOIs
StatePublished - Jul 2019
Externally publishedYes
Event17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019 - Shenzhen, China
Duration: Jul 1 2019Jul 3 2019

Publication series

Name2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019

Conference

Conference17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019
CountryChina
CityShenzhen
Period7/1/197/3/19

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Keywords

  • Density Matrix
  • Quantum Mechanics
  • Sexual Harassment
  • Text Classification

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Information Systems

Cite this

Yan, P., Li, L., Chen, W., & Zeng, D. (2019). Quantum-inspired density matrix encoder for sexual harassment personal stories classification. In X. Zheng, A. Abbasi, M. Chau, A. Wang, & L. Zhou (Eds.), 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019 (pp. 218-220). [8823281] (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISI.2019.8823281