Construction and design of intelligent retrieval systems for materials databases in the big data environment
Yaran Wang
University of Science and Technology Beijing (USTB)
Qiaoyang Ji
University of Science and Technology Beijing (USTB)
Zuxiang Tan
School of Materials Science & Engineering, USTB
Zhengfei Ye
School of Mathematics and Physics
Zhenyan Zhou
School of Advanced Engineering
DOI: https://doi.org/10.59429/esta.v11i4.8465
Keywords: Big Data; Materials Database; Intelligent Retrieval System
Abstract
With the booming development of big data technology, the field of materials science is undergoing a profound transformation from traditional research paradigms to data-driven ones. As a crucial infrastructure for materials science research, the construction of materials databases and the design of intelligent retrieval systems have become hot topics in current research. This paper reviews the construction techniques of materials databases, the design and implementation of intelligent retrieval systems, and the major development trends in this field under the big data environment. Firstly, the paper introduces the importance of materials databases in the context of big data and the key technologies involved in their construction. Subsequently, it elaborates on the core algorithms, user interface design, and system performance optimization of intelligent retrieval systems. Furthermore, the paper summarizes the main achievements and progress of existing research and points out potential directions for future research. The review aims to provide valuable references and insights for researchers in the field of materials databases and intelligent retrieval systems.
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[8] The authors contribute equally.