Multi-dependent Latent Dirichlet Allocation

Wei Cheng Hsin, Jen Wei Huang

研究成果: Conference contribution

摘要

Latent Dirichlet Allocation (LDA) is an attractive topic model research because LDA is so flexible for solving different problems. Because of its different core dependencies, it can be applied to many topics, such as emotion detection, information systems or image clustering. In recent works, researchers have focused on novel dependency to obtain perfect fitting to datasets. However, real world data is too diverse and abundant to be fitted with one single dependency. A single dependency model can only concentrate on the overall characteristic of datasets and thus ignores small details in the data. In addition, model selection for different situation is always difficult. As a result, we propose Multi-dependent Latent Dirichlet Allocation (MD-LDA). MD-LDA can be applied various dependencies into the model. We don't need to select a specific model. For each piece of data, MD-LDA can pick up the most optimal fitting dependency from the dependency set and therefore obtain the best dependencies for the dataset. We also apply some previous works into MD-LDA as a basis for comparison. In our experiments, MD-LDA exhibits the best performance in various cases and is an improvement compared to the other models under consideration.

原文English
主出版物標題Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017
發行者Institute of Electrical and Electronics Engineers Inc.
頁面154-159
頁數6
ISBN(電子)9781538642030
DOIs
出版狀態Published - 2018 5月 9
事件2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017 - Taipei, Taiwan
持續時間: 2017 12月 12017 12月 3

出版系列

名字Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017

Other

Other2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017
國家/地區Taiwan
城市Taipei
期間17-12-0117-12-03

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 電腦科學應用
  • 人機介面

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