Analysing the Resourcefulness of the Paragraph for Precedence Retrieval
July 29, 2023 Β· Declared Dead Β· π International Conference on Artificial Intelligence and Law
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Authors
Bhoomeendra Singh Sisodiya, Narendra Babu Unnam, P. Krishna Reddy, Apala Das, K. V. K. Santhy, V. Balakista Reddy
arXiv ID
2308.01203
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL
Citations
0
Venue
International Conference on Artificial Intelligence and Law
Last Checked
4 months ago
Abstract
Developing methods for extracting relevant legal information to aid legal practitioners is an active research area. In this regard, research efforts are being made by leveraging different kinds of information, such as meta-data, citations, keywords, sentences, paragraphs, etc. Similar to any text document, legal documents are composed of paragraphs. In this paper, we have analyzed the resourcefulness of paragraph-level information in capturing similarity among judgments for improving the performance of precedence retrieval. We found that the paragraph-level methods could capture the similarity among the judgments with only a few paragraph interactions and exhibit more discriminating power over the baseline document-level method. Moreover, the comparison results on two benchmark datasets for the precedence retrieval on the Indian supreme court judgments task show that the paragraph-level methods exhibit comparable performance with the state-of-the-art methods
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