数据资产的检索方法、电子设备及计算机可读存储介质
By training an extreme gradient boosting algorithm model and pre-setting target retrieval parameters, the algorithm generates retrieval statements and outputs retrieval results in a preset order. This solves the problem that users find it difficult to quickly locate target data assets in a big data environment, and improves retrieval efficiency and data asset utilization efficiency.
CN115328945BActive Publication Date: 2026-07-17PING AN TECH (SHENZHEN) CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- PING AN TECH (SHENZHEN) CO LTD
- Filing Date
- 2022-08-16
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
In a big data environment, existing technologies make it difficult for users to quickly locate target data assets, especially when the search results exceed three pages, which affects user efficiency.
Method used
The extreme gradient enhancement algorithm model is used to preset target retrieval parameters. The model is trained based on users' historical retrieval data and asset feature tags to generate retrieval statements and output retrieval results in a preset order related to the target asset feature information.
Benefits of technology
It improves the first-page hit rate of search results, helps users quickly locate target data assets, improves user data utilization efficiency, and supports enterprise data value mining and business decision-making.
✦ Generated by Eureka AI based on patent content.
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Figure CN115328945B_ABST
Abstract
本申请公开了一种数据资产的检索方法、电子设备及计算机可读存储介质。所述检索方法包括：接收并响应用户的检索指令，确定待检索的数据资产；基于利用极端梯度增强算法模型预设的目标检索参数和所述待检索的数据资产的关键字信息，生成检索语句；其中，所述目标检索参数为对所述待检索的数据资产成为目标数据资产具有预设影响程度的目标资产特征信息；利用所述检索语句对所述待检索的数据资产进行检索，按与所述目标资产特征信息相关的预设顺序输出检索结果。上述方案，能够实现在用户检索时智能排序的效果，辅助用户快速定位目标数据资产，极大程度的提升用户的用数效率。
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