基于知识图谱与语义计算的智能信息搜索技术研究

Intelligent Information Search Technology Based on Knowledge Graph and Semantic Computing

面向信息搜索的智能需求,分析智能信息搜索的特征,研究面向应用领域表征的知识图谱构建,提出一种带约束的语义相似模型和隐性反馈修正机制,探索特定条件下智能信息搜索的实现途径。通过地理环境应用领域的原型实验数据分析,发现基于知识图谱与语义计算的信息搜索准确率可达85%,具有较强的实用性,可为垂直搜索应用领域的技术优化提供参考思路。

In the face of intelligent demand for information search,this paper analyzes the characteristics of intelligent information search,studies the construction of knowledge graph for the representation of application domain,proposes a constrained semantic similarity model and a recessive feedback correction mechanism,and explores the realization ways of intelligent information search under specific conditions. From the experimental data in the field of geographical environment application,it is found that the accuracy of information search based on knowledge graph and semantic computing can reach 85%,which has strong practicability and can provide a reference for technology optimization in the field of vertical search application.