首页> 外文会议>International Conference on Swarm Intelligence >A Knowledge Graph Enhanced Semantic Matching Method for Plan Recommendation
【24h】

A Knowledge Graph Enhanced Semantic Matching Method for Plan Recommendation

机译:一种知识图增强的计划推荐语义匹配方法

获取原文

摘要

In order to solve the problem of rapid matching and optimization of the plan, a semantic feature-based smart matching method of the plan is proposed, which can be used to solve the problem of the typical small sample date for recommendation of the best plan in the military field. In this method, the semantic feature of the battle plan is established to describe the combat scenario through a military knowledge graph. The semantic feature annotation of the plan is constructed based on the military knowledge map too. So the semantic features corresponding to each matching target plan object are described, which realize the explicit definition of the hidden knowledge of the combat plan. Based on knowledge enhancement technology, the similarity measurement of semantic features is calculated, realizing the intelligent semantic matching of combat plans, so as to solve the problem of low matching efficiency and accuracy based on pragmatic level features such as index or keywords, satisfy the rapid matching and precise recommendation of plans.
机译:为了解决方案的快速匹配和优化问题,提出了一种基于语义特征的方案智能匹配方法,用于解决军事领域推荐最佳方案的典型小样本数据问题。该方法建立了作战计划的语义特征,通过军事知识图来描述作战场景。该方案的语义特征标注也是基于军事知识地图构建的。描述了每个匹配目标计划对象对应的语义特征,实现了作战计划隐藏知识的显式定义。基于知识增强技术,计算语义特征的相似度,实现作战计划的智能语义匹配,以解决基于索引或关键字等实用级特征的匹配效率和准确性低的问题,满足计划的快速匹配和精确推荐。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号