%0 Journal Article
%T 一种基于相似度计算的实体数据关系归属方法<br>A Relationship Attribution Method for Entity Data Based on Similarity Calculation
%A 冒鸿宇
%A 孙刘杰
%A 朱衍熹
%J Operations Research and Fuzziology
%P 230-237
%@ 2163-1530
%D 2024
%I Hans Publishing
%R 10.12677/orf.2024.145465
%X 特定领域的数据蕴含了大量有价值的知识及关系划分&#65292;从中能正确将其进行关系划分一直是一个值得关注的话题。当前关系划分都依赖于大量样本模型进行训练得出&#65292;由于特定领域的实体数据关系样本数量较少&#65292;显然应用到特定领域中存在局限。因此本文针对该问题&#65292;提出一种基于相似度计算的实体数据关系归属方法&#65292;其中建立一个特定领域的少样本实体关系术语树&#65292;与待划分的实体数据进行相似度计算得到在树中具体位置&#65292;从而解决错误归属问题&#65292;显著减少人工管理成本&#65292;能够有效提升系统的可用性。<br>Domain-specific data contains a large amount of valuable knowledge and relationship delineation, from which it is always a topic of interest to be able to correctly perform relationship delineation. Currently, the relationship classification relies on a large number of sample models for training, due to the small number of domain-specific entity data relationship samples, it is obvious that there are limitations in applying to specific domains. Therefore, in this paper, we propose a similarity-based relationship attribution method for entity data, in which a domain-specific entity relationship term tree with few samples is established, and the entity data to be partitioned is similarity-calculated to get the specific position in the tree, thus solving the problem of misattribution, significantly reducing the cost of manual management, and effectively improving the usability of the system.
%K 相似度计算&#65292
%K 实体关系&#65292
%K 实体归属&#65292
%K 实体数据<br>Similarity Calculation
%K Entity Relationship
%K Entity Attribution
%K Entity Data
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=97565