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Category: Databases

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This AI Paper from Microsoft Introduces a DiskANN-Integrated System: A Cost-Effective and Low-Latency Vector Search Using Azure Cosmos DB
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This AI Paper from Microsoft Introduces a DiskANN-Integrated System: A Cost-Effective and Low-Latency Vector Search Using Azure Cosmos DB

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The ability to search high-dimensional vector representations has become a core requirement for modern data systems. These vector representations, generated […]

PilotANN: A Hybrid CPU-GPU System For Graph-based ANNS
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PilotANN: A Hybrid CPU-GPU System For Graph-based ANNS

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Approximate Nearest Neighbor Search (ANNS) is a fundamental vector search technique that efficiently identifies similar items in high-dimensional vector spaces. […]

Weaviate Researchers Introduce Function Calling for LLMs: Eliminating SQL Dependency to Improve Database Querying Accuracy and Efficiency
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Weaviate Researchers Introduce Function Calling for LLMs: Eliminating SQL Dependency to Improve Database Querying Accuracy and Efficiency

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Databases are essential for storing and retrieving structured data supporting business intelligence, research, and enterprise applications. Querying databases typically requires […]

This AI Paper Propose SHARQ: An Efficient AI Framework for Quantifying Element Contributions in Association Rule Mining
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This AI Paper Propose SHARQ: An Efficient AI Framework for Quantifying Element Contributions in Association Rule Mining

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Data mining is vital for uncovering meaningful patterns and relationships within large datasets. These insights enable informed decision-making across diverse […]

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