Unsupervised Legal Case Retrieval Based on Multi-granularity Semantic-Aware Interaction
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This work is supported by SIAT-DELI Artificial Intelligence and Law Lab (Y9Z028)

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    Abstract:

    With the ever-increasing size of legal cases in China, relevant legal case retrieval given a user query has attracted considerable attention. Conventional keyword-based retrieval systems look for matching cases that contain one or more words specified by the user. However, keyword searching is sharply focused on finding the exact terms specified in the query, making the retrieval systems miss many relevant documents. On the other hand, semantic-aware information retrieval methods usually rely heavily

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ZHOU Xianhang, SHEN Yanyan. Unsupervised Legal Case Retrieval Based on Multi-granularity Semantic-Aware Interaction[J]. Journal of Integration Technology,2022,11(2):55-66

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  • Received:
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  • Online: March 22,2022
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