Topic Modelling Meets Deep Neural Networks: A Survey

被引:0
|
作者
Zhao, He [1 ]
Dinh Phung [1 ,2 ]
Viet Huynh [1 ]
Jin, Yuan [1 ]
Du, Lan [1 ]
Buntine, Wray [1 ]
机构
[1] Monash Univ, Dept Data Sci & Artificial Intelligence, Melbourne, Vic, Australia
[2] VinAI Res, Hanoi, Vietnam
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Topic modelling has been a successful technique for text analysis for almost twenty years. When topic modelling met deep neural networks, there emerged a new and increasingly popular research area, neural topic models, with nearly a hundred models developed and a wide range of applications in neural language understanding such as text generation, summarisation and language models. There is a need to summarise research developments and discuss open problems and future directions. In this paper, we provide a focused yet comprehensive overview of neural topic models for interested researchers in the AI community, so as to facilitate them to navigate and innovate in this fast-growing research area. To the best of our knowledge, ours is the first review on this specific topic.
引用
收藏
页码:4713 / 4720
页数:8
相关论文
共 50 条
  • [31] Survey of Deep Learning Neural Networks Implementation on FPGAs
    Tourad, El Hadrami Cheikh
    Eleuldj, Mohsine
    PROCEEDINGS OF 2020 5TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND ARTIFICIAL INTELLIGENCE: TECHNOLOGIES AND APPLICATIONS (CLOUDTECH'20), 2020, : 137 - 144
  • [32] A Survey on Leveraging Deep Neural Networks for Object Tracking
    Krebs, Sebastian
    Duraisamy, Bharanidhar
    Flohr, Fabian
    2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2017,
  • [33] A survey of the recent architectures of deep convolutional neural networks
    Khan, Asifullah
    Sohail, Anabia
    Zahoora, Umme
    Qureshi, Aqsa Saeed
    ARTIFICIAL INTELLIGENCE REVIEW, 2020, 53 (08) : 5455 - 5516
  • [34] Structural-topic aware deep neural networks for information cascade prediction
    Zhou, Bangzhu
    Feng, Xiaodong
    Feng, Hemin
    PEERJ COMPUTER SCIENCE, 2024, 10
  • [35] Topic Predictions and Optimized Recommendation Mechanism Based on Integrated Topic Modeling and Deep Neural Networks in Crowdfunding Platforms
    Shafqat, Wafa
    Byun, Yung-Cheol
    APPLIED SCIENCES-BASEL, 2019, 9 (24):
  • [36] Fitting deep neural networks into the statistical regression modelling setting
    Ha, Il Do
    Burke, Kevin
    JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE, 2024,
  • [37] A survey on face data augmentation for the training of deep neural networks
    Xiang Wang
    Kai Wang
    Shiguo Lian
    Neural Computing and Applications, 2020, 32 : 15503 - 15531
  • [38] Saving Memory Space in Deep Neural Networks by Recomputing: A Survey
    Ulidowski, Irek
    REVERSIBLE COMPUTATION, RC 2023, 2023, 13960 : 89 - 105
  • [39] Learning From Noisy Labels With Deep Neural Networks: A Survey
    Song, Hwanjun
    Kim, Minseok
    Park, Dongmin
    Shin, Yooju
    Lee, Jae-Gil
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (11) : 8135 - 8153
  • [40] Adversarial Attacks and Defenses Against Deep Neural Networks: A Survey
    Ozdag, Mesut
    CYBER PHYSICAL SYSTEMS AND DEEP LEARNING, 2018, 140 : 152 - 161