基于语义树的语义关联度算法改进  

Improvement of semantic association algorithms based on semantic tree

作　　者：孟凡荣[1] 田恬[1] 张磊[1] 

机构地区：[1]徐州中国矿业大学计算机科学与技术学院,江苏221008

出　　处：《微计算机信息》2009年第12期268-270,共3页Control & Automation

摘　　要：某项目平台中存在大量用户数据,由于数据的复杂性,采用传统的语义相关度计算方法无法准确获得所需要的用户信息。本文针对这个问题,对数据构建语义树,改进了现有的计算语义联系的方法,在原有的计算方法基础上,加入了上下文权重描述数据之间的语义联系。本文方法可以更好的对用户的查询请求进行概念扩充,从而找出相关数据,满足用户的检索需求。There is a large number of user data in certain platform. Because of the complexity, it is difficult to get the users’ information in need by traditional semantic association calculation method. So a semantic tree is built to overcome that in this paper. Context weight is added to improve the existing method of semantic associations. Also the original calculation method is integrated to describe the semantic association between data. With that, the user’s request can be expanded better, which is helpful to meet the users’ need.

关 键 词：语义检索 语义关联 概念扩充 权重 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]