This was a high-stakes implementation of advanced data pipelines designed with zero tolerance for data inconsistency or ...

This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in ...

This paper deeply discusses the storage and query optimization algorithm of distributed database for big data. Firstly, the importance of distributed database storage optimization is analyzed, and key ...

SHENZHEN, China, Jan. 2, 2025 /PRNewswire/ -- MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the development of an innovative hybrid algorithm that combines the ...

The Multi-Query Optimization (MQO) problem is a class of data-intensive problems that are NP-hard, and it has applications in many fields such as database query optimization, machine learning ...

The Multi-Query Optimization (MQO) problem is a class of data-intensive problems that are NP-hard, and it has applications in many fields such as database query optimization, machine learning ...

A task scheduling algorithm optimization model based on SVM, KNN, and fuzzy comprehensive evaluation was designed to effectively meet the localization requirements in big data processing. 3 Overview ...

Abstract With the rapid development of artificial intelligence, large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. These models ...

This paper concentrates on the problem of embedded database query optimization, which is a crucial problem in embedded system design. Firstly, we describe the s ...