用户相关反馈下的空间关键字语义查询方法  

User-related Feedback Based Personalized Spatial Keyword Semantic Query Approach

作　　者：孟祥福[1] 赵路路 张霄雁[1] 李盼 MENG Xiang-fu;ZHAO Lu-lu;ZHANG Xiao-yan;LI Pan(School of Electronic and Information Engineering,Liaoning Technical University,Huludao 125105,China)

机构地区：[1]辽宁工程技术大学电子与信息工程学院

出　　处：《小型微型计算机系统》2019年第12期2650-2656,共7页Journal of Chinese Computer Systems

基　　金：国家自然科学基金面上项目(61772249)资助

摘　　要：现有的空间关键字查询方法通常根据查询关键字在空间对象文本信息中的出现频率进行文本相关度评估,没有考虑用户对不同查询关键字的偏好程度,并且也没有考虑语义相关性.为解决上述问题,本文提出一种基于用户相关反馈的空间关键字个性化语义查询方法.该方法分为离线处理和在线处理两个阶段,在离线处理阶段,采用Gibbs算法估计空间对象文本信息的主题概率分布,进而利用LDA模型对空间数据集进行语义扩展.在线查询处理阶段,对于用户的初始查询条件,首先利用IR-tree混合索引结构从扩展后的空间数据库中获得候选查询结果;然后,用户根据个人偏好在候选集中明确标注出相关的查询结果(即相关反馈),根据用户的反馈信息,采用Rocchio算法对用户初始查询条件进行更新,使得新的查询条件更贴近用户实际需求和偏好;利用更新后的查询条件再进行检索,从而得到新的候选集,重复执行反馈过程,直到查询结果令用户满意为止.实验结果表明,本文提出的基于用户相关反馈的空间关键字语义查询方法可以有效捕获用户隐式偏好并体现语义相关性,在一定程度上提高了空间关键字查询结果的个性化程度和准确率.Existing spatial keyword query methods usually evaluate text relevance according to the frequency of occurrence of query keywords in spatial object text information,without considering the degree of preference of users to different query keywords,and without considering semantic relevance.To solve the above problems,this paper proposes A User-related feedback based Personalized Spatial Keyword Semantic Query Approach.This method is divided into two stages,offline processing and online processing.In the offline processing stage,Gibbs algorithm is used to estimate the thematic probability distribution of spatial object text information,and then LDA model is used to extend the spatial data set semantically.In the online query processing stage,for the initial query conditions of users,the IR-tree hybrid index structure is first used to obtain candidate query results from the expanded spatial database.Then,the user clearly marked relevant query results(i.e.relevant feedback)in the candidate set according to his/her preferences.According to the user’s feedback information,Rocchio algorithm was adopted to update the user’s initial query conditions,so that the new query conditions were closer to the user’s actual needs and preferences.The updated query condition is then retrieved to obtain a new candidate set and the feedback process is repeated until the query result is satisfactory to the user.Experimental results show that the proposed A User-related feedback based Personalized Spatial Keyword Semantic Query Approach can effectively capture users’implicit preferences and embody semantic relevance,which to some extent improves the personalized degree and accuracy of spatial keyword query results.

关 键 词：空间数据库 Rocchio算法 IR-tree混合索引结构 用户反馈 top-k排序 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]