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Dhara retrieval engine enhances Indian Knowledge Systems search

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Dhara, a novel retrieval engine designed to efficiently search Indian Knowledge Systems (IKS). This system integrates hybrid search, entity notes, fuzzy verse retrieval, and neural reranking to locate relevant evidence that may be scattered across various texts, including verses, translations, and commentaries. Evaluations show that Dhara's BGE-M3 embedding model outperforms traditional BM25, and the inclusion of entity notes and fuzzy verse retrieval further enhances retrieval accuracy across different categories. AI

IMPACT This system could improve access to and understanding of historical and cultural knowledge bases through advanced AI-driven search.

RANK_REASON The cluster describes a new research paper detailing a novel information retrieval system. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

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

Dhara retrieval engine enhances Indian Knowledge Systems search

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The cluster describes a new research paper detailing a novel information retrieval system. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Mohan Raghavan ·

    Dhara: Evidence-Oriented Retrieval for Indian Knowledge Systems

    Relevant evidence in Indian Knowledge Systems (IKS) collections may be distributed across passages in different parts of a work, including verses, translations, and commentaries. Locating it requires matching natural-language questions and partially remembered verse fragments to …

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