Sunday, June 22, 2025

How Deep Transfer Learning is Revolutionizing Online Civil Dispute Consultations! #Sciencefather #researchawards #deeplearning


The rapid increase in civil disputes and the limited capacity of legal systems have challenged the effectiveness of traditional dispute resolution methods. Online Dispute Resolution (ODR) platforms—such as China’s Internet Court, British Columbia’s Civil Resolution Tribunal, and the UK’s Online Court—have emerged as promising solutions. A core component of these platforms is the Classification of Online Consultation (COC), which helps route civil legal questions to the appropriate departments. However, manual classification is inefficient and error-prone, especially as civil disputes become more diverse and complex.


COC tasks rely heavily on text classification, but several issues hinder accurate results. Many platforms lack sufficient and balanced training data, while the short, colloquial, and vague nature of users’ input makes it difficult for traditional machine learning models to perform well. Additionally, the use of Chinese text introduces further complexity due to limited labeled data and grammatical challenges. These factors collectively result in poor classification accuracy and hinder the effectiveness of civil dispute resolution services online.


To address these challenges, the study introduces a deep transfer learning-based classification method called CMDTL (Cross-platform Mapping with Deep Transfer Learning). By transferring knowledge from richer data sources and applying advanced techniques like joint distribution adaptation and improved marginal Fisher analysis, this method significantly improves accuracy despite limited and unbalanced data. It also uses ontology modeling to clarify legal concepts, ensuring a more accurate understanding of the user’s legal queries. This approach ultimately aims to enhance the efficiency and precision of online civil dispute consultations.

 

International Conference on Computer Vision


The International Research Awards on Computer Vision recognize groundbreaking contributions in the field of computer vision, honoring researchers, scientists and innovators whose work has significantly advanced the domain. This prestigious award highlights excellence in fundamental theories, novel algorithms and real-world applications, fostering progress in artificial intelligence, image processing and deep learning.


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