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This study proposes a new approach for identifying relevant articles based on transactions or occurrences. The primary objective of this study is to determine which legal articles can serve as claims or counterarguments given a specific transaction or a particular occurrence. To achieve this, we analyze judicial judgments and assess the relevance between the predicted and actual cited articles. Based on empirical observations from preliminary research, we identify candidate articles using two main approaches: a nearest-neighbor approach and a distance-based method. Furthermore, we investigate we can use hybrid method to optimize the performance and provide a simple implementation of our work on recommendation system, which has the potential for widespread application among both the general public and law firms.

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Nearest-Neighbor Search or Distance-Based Search, Which is Better for Finding Relevant Articles?

  • 会议论文

  • 发表日期：

    2025年

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  • Ho-Chien Huang,
  • Chao-Lin Liu

摘要

This study proposes a new approach for identifying relevant articles based on transactions or occurrences. The primary objective of this study is to determine which legal articles can serve as claims or counterarguments given a specific transaction or a particular occurrence. To achieve this, we analyze judicial judgments and assess the relevance between the predicted and actual cited articles. Based on empirical observations from preliminary research, we identify candidate articles using two main approaches: a nearest-neighbor approach and a distance-based method. Furthermore, we investigate we can use hybrid method to optimize the performance and provide a simple implementation of our work on recommendation system, which has the potential for widespread application among both the general public and law firms.