基于时空约束和成本感知的集合空间关键字查询  

Collective Spatial Keyword Query Based on Time-Distance Constrained and Cost Aware

作　　者：李松[1] 曹文琪 郝晓红[1] 张丽平[1] 郝忠孝[1] Li Song;Cao Wenqi;Hao Xiaohong;Zhang Liping;Hao Zhongxiao(School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080)

机构地区：[1]哈尔滨理工大学计算机科学与技术学院,哈尔滨150080

出　　处：《计算机研究与发展》2025年第3期808-819,共12页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(62072136);黑龙江省重点研发计划项目(JD2023SJ20);国家重点研发计划项目(2020YFB1710200)。

摘　　要：集合空间关键字查询在空间数据库、位置服务、智能推荐和群智感知等领域具有重要的作用.现有的集合空间关键字查询方法没有考虑要求同时带有时空约束和成本感知的问题,不能满足大部分用户在时空约束条件下的查询需求问题,已有研究成果具有较大的局限性.为了弥补已有方法的不足,提出一种基于时空约束和成本感知的集合空间关键字查询TDCCA-Co SKQ.为了解决现有索引中无法同时包含关键字信息和时间信息的问题,提出了一种TDCIR-Tree索引,该索引融合了倒排文件和时间属性标签文件,可以减小查询计算的开销;为了有效地筛选出符合查询条件的集合,提出了一种TDCCA_PP算法,其中包括第1层剪枝算法、组间有序排列和第2层剪枝算法,可以提高关键字的查询效率;进一步提出了一种基于TDC成本函数的排序算法,TDC成本函数是由距离成本和时间成本组成的,其中包含代表用户偏好度的自变量系数α和β,可以增加用户的选择自由度,有效解决了现有的成本函数无法满足时空约束和成本感知的集合空间关键字查询的问题.理论研究与实验表明,所提出的方法具有较好的效率与准确性.Collective spatial keyword queries play an important role in the fields such as spatial databases,location services,intelligent recommendations,and group intelligence perception.The existing collective spatial keyword query methods do not consider the problem of requiring time-distance constrained and cost aware,and cannot meet the query needs of most users under time-distance constrained.Existing research results have significant limitations.To make up for the shortcomings of existing methods,collective spatial keyword query based on time-distance constrained and cost aware(called TDCCA-CoSKQ)is proposed.To address the issue of not being able to include both keyword information and time information in existing indexes,the TDCIR-Tree index is proposed,which combines inverted files and time attribute label files.TDCIR-Tree can reduce the cost of query calculation.TDCCA_PP algorithm is proposed to address the issue of subsequent screening of collections that meet query criteria for TDCCA-CoSKQ,including TDCCAPruning1,TDCCAPermutation,and TDCCAPruning2,and it can improve the efficiency of keyword queries.The TDC cost function and its corresponding sorting algorithm are proposed.The TDC cost function is composed of distance cost and time cost,which includes independent variable coefficients representing user preferenceαandβ,and it can increase users’freedom of choice.The problem of existing cost functions not meeting the collective spatial keyword query based on time-distance constrained and cost aware is effectively solved.Theoretical research and experiments have shown that the proposed method has good efficiency and accuracy.

关 键 词：集合空间关键字查询 时空约束 成本感知 倒排文件 时间属性标签文件 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]