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Research Paper | Computer Science | Volume 14 Issue 5, May 2025 | Pages: 1391 - 1396 | United States
AI-Driven Knowledge Graphs for Enterprise Search - Enhancing Enterprise-Wide Search and Recommendations with AI
Abstract: The paper addresses implementation challenges, such as data integration, scalability, and security considerations in enterprise environments. Finally, we explore emerging trends, such as generative AI and self-evolving knowledge graphs, that are shaping the future of enterprise search. By adopting AI-driven knowledge graphs, organizations can significantly enhance their internal search capabilities, enabling more efficient decision-making and collaboration.
Keywords: AI-driven knowledge graphs, enterprise search, data integration, generative AI, scalable architecture
How to Cite?: Mohit Thodupunuri, "AI-Driven Knowledge Graphs for Enterprise Search - Enhancing Enterprise-Wide Search and Recommendations with AI", Volume 14 Issue 5, May 2025, International Journal of Science and Research (IJSR), Pages: 1391-1396, https://www.ijsr.net/getabstract.php?paperid=SR25521024520, DOI: https://dx.doi.org/10.21275/SR25521024520