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Brazilian legal document retrieval improved by structural segmentation

Researchers have explored structural segmentation as a method to enhance the retrieval of Brazilian legal documents. By breaking down long legal texts into smaller, hierarchical chunks such as articles and non-normative components, the study found that this approach improves dense retrieval models. While this segmentation significantly increases the number of indexed units, it yields comparable or better results than whole-document indexing, particularly when core chunks are enriched with metadata. The findings suggest that a full hierarchical representation is not essential for effective retrieval. AI

IMPACT This research could lead to more effective AI-powered legal search tools by improving how legal documents are processed and indexed.

RANK_REASON Academic paper on information retrieval techniques. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Brazilian legal document retrieval improved by structural segmentation

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Academic paper on information retrieval techniques. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 Română(RO) · Jayr Pereira ·

    Structural Segmentation for Brazilian Legal Document Retrieval

    Long legal documents are often represented as single retrieval units, which can dilute relevant content and limit retrieval effectiveness. This study investigates structural segmentation as a document representation strategy to improve Brazilian legal document retrieval. Using th…