以民事訴訟之爭點分群為基礎的類似案件搜尋系統

Clustering Issues in Civil Judgments for Recommending Similar Cases

類似案件搜尋是法律實務中十分重要的任務，從中能獲取珍貴的法律見解。而爭點是民事訴訟中兩造互為對立的主張，代表審理案件時要考慮的核心事項。許多研究以不同角度計算判決書間相似度；而我們提出以爭點的分群編碼判決書的方法，來建構一個類似案件搜尋系統。我們以具有法律背景的人工評分來驗證系統的有效性，同時比較數種前處理程序和分群方法不同組合所達成的效果。

Similar judgments search is an important task in legal practice, from which valuable legal insights can be obtained. Issues are disputes between both parties in civil litigation, which represents the core topics to be considered in the trials. Many studies calculate the similarity between judgments from different perspectives and methods. We first cluster the issues in the judgments, and then encode the judgments with vectors for whether or not the judgments contain issues in the corresponding clusters. The similarity between the judgments are evaluated based on the encoded messages. We verify the effectiveness of the system with a human scoring process by a legal background assistant, while comparing the effects of several combinations of preprocessing steps and selections of clustering strategies.