Application of Deep Learning Technology in the Recommendation System of Constitutional and Constitutional Cases. (21st September 2022)
- Record Type:
- Journal Article
- Title:
- Application of Deep Learning Technology in the Recommendation System of Constitutional and Constitutional Cases. (21st September 2022)
- Main Title:
- Application of Deep Learning Technology in the Recommendation System of Constitutional and Constitutional Cases
- Authors:
- Wu, Zhongbo
Lu, Yuan
Feng, Zijun - Other Names:
- Lakshmanna Kuruva Academic Editor.
- Abstract:
- Abstract : Due to the huge system in the field of constitution, the content of cases is complicated, and the number of documents related to constitutional cases is huge. It is incredibly tough to find the information that suits your demands in such a large volume of constitutional documents. The artificial neural network-based deep learning method has made significant progress. Deep learning has been used in the disciplines of computer image and video processing, as well as natural language processing, and has outperformed typical machine learning methods. To that purpose, the content-based recommendation algorithm in this work is improved using deep learning approaches. This paper primarily covers the following topics: (1) the current research status of deep learning technology in recommender systems is reviewed, and the theoretical knowledge of deep neural networks is introduced. (2) A text classification model OCCNN based on character-level convolutional neural network is proposed to solve the problem of document classification of massive cases. A semantic similarity calculation model TF-W2V based on word frequency and word vector is also proposed to solve the problem of semantic similarity calculation of cases. (3) The two methods are tested, and the experimental results show that the accuracy is much higher than that of the conventional method. The model can recommend cases that meet the needs of users according to the requirements put forward by users in the process ofAbstract : Due to the huge system in the field of constitution, the content of cases is complicated, and the number of documents related to constitutional cases is huge. It is incredibly tough to find the information that suits your demands in such a large volume of constitutional documents. The artificial neural network-based deep learning method has made significant progress. Deep learning has been used in the disciplines of computer image and video processing, as well as natural language processing, and has outperformed typical machine learning methods. To that purpose, the content-based recommendation algorithm in this work is improved using deep learning approaches. This paper primarily covers the following topics: (1) the current research status of deep learning technology in recommender systems is reviewed, and the theoretical knowledge of deep neural networks is introduced. (2) A text classification model OCCNN based on character-level convolutional neural network is proposed to solve the problem of document classification of massive cases. A semantic similarity calculation model TF-W2V based on word frequency and word vector is also proposed to solve the problem of semantic similarity calculation of cases. (3) The two methods are tested, and the experimental results show that the accuracy is much higher than that of the conventional method. The model can recommend cases that meet the needs of users according to the requirements put forward by users in the process of handling cases. … (more)
- Is Part Of:
- Wireless communications and mobile computing. Volume 2022(2022)
- Journal:
- Wireless communications and mobile computing
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09-21
- Subjects:
- Wireless communication systems -- Periodicals
Mobile communication systems -- Periodicals
621.38205 - Journal URLs:
- https://onlinelibrary.wiley.com/journal/15308677 ↗
https://www.hindawi.com/journals/wcmc/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1155/2022/8444672 ↗
- Languages:
- English
- ISSNs:
- 1530-8669
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9323.860000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24060.xml