Confidential — Stefan Michaelcheck Only

"AyurKOSH Dataset_ A Machine-Readable Ayurvedic Knowledge Resource for Knowledge Graph and Computational Intelligence"

2026resource releaseapplicationdataset

Sharayu Mirasdar, Yash Gujar, Harish Patankar, Mangesh Bedekar

IEEE DataPort

https://doi.org/10.21227/58ej-wz87OpenAlex: W7118129985
1
URLs Found
0
Internal Citations
4
Authors
usable
Abstract Quality
GPT-5.5 Abstract Analysis

Problems Identified (2)

Unstructured Ayurvedic Knowledge: Classical Ayurvedic texts contain interconnected medical knowledge but remain largely unstructured and inaccessible for computational analysis.

Unstructured Ayurvedic Knowledge: Classical Ayurvedic texts contain interconnected medical knowledge but remain largely unstructured and inaccessible for computational analysis.

Proposed Solutions (4)

AyurKOSH Ayurvedic Knowledge Graph Dataset: The work presents AyurKOSH, a machine-readable Ayurvedic dataset designed as a knowledge graph with structured entities and semantic relationships from classical Ayurvedic texts and curated sources.

Ayurvedic Pharmacology and Substitution Metadata: The dataset includes structured disease, symptom, formulation, herbal component, pharmacological, botanical, and herb-substitution information.

AyurKOSH Ayurvedic Knowledge Graph Dataset: The work presents AyurKOSH, a machine-readable Ayurvedic dataset designed as a knowledge graph with structured entities and semantic relationships from classical Ayurvedic texts and curated sources.

Ayurvedic Pharmacology and Substitution Metadata: The dataset includes structured disease, symptom, formulation, herbal component, pharmacological, botanical, and herb-substitution information.

Results (3)

Supports AI and NLP Applications:

Academic Noncommercial Availability:

Supports AI and NLP Applications:

Research Domain

Computational Ayurveda / biomedical knowledge graphs

← Back to all papers