[1]孟祥福,赖贞祥,崔江燕.集合空间关键字内聚组查询方法[J].智能系统学报,2024,19(3):707-718.[doi:10.11992/tis.202211013]
MENG Xiangfu,LAI Zhenxiang,CUI Jiangyan.Cohesive group query approach for collective spatial keywords[J].CAAI Transactions on Intelligent Systems,2024,19(3):707-718.[doi:10.11992/tis.202211013]
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MENG Xiangfu,LAI Zhenxiang,CUI Jiangyan.Cohesive group query approach for collective spatial keywords[J].CAAI Transactions on Intelligent Systems,2024,19(3):707-718.[doi:10.11992/tis.202211013]
集合空间关键字内聚组查询方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
19
期数:
2024年第3期
页码:
707-718
栏目:
学术论文—自然语言处理与理解
出版日期:
2024-05-05
- Title:
- Cohesive group query approach for collective spatial keywords
- Keywords:
- collective spatial keyword query; cohesive group query; road network; social network; core-tree structure; road network index; sliding window; point of interest
- 分类号:
- TP311
- 文献标志码:
- 2023-09-14
- 摘要:
- 给定一个道路网络和社交网络，集合空间关键字查询的目的是找到一组兴趣点，该组兴趣点的文本信息包含所有查询关键字，与查询的位置较近且彼此之间的距离较小。内聚组查询的目的是找到在地理位置和社交关系上紧密联系的一组用户；而集合空间关键字内聚组查询的目的是找到满足查询要求的一对最佳匹配的兴趣点集合和用户集合。针对这一问题，提出一种新的集合空间关键字内聚组查询处理模式。首先通过快速贪心查询过程获得候选兴趣点集合，然后使用core-tree结构存储(k,c)-core核心分解的结果，从而提高内聚组查询效率，并且保证查询结果能够同时满足用户之间的社会关系约束和兴趣点之间的空间位置约束。通过在真实数据集上开展实验，结果表明提出的方法比枚举方法的查询效率快1~2个数量级，并且具有较高查询准确性。
- Abstract:
- Given a road network and a social network, the collective spatial keyword query aims to find a set of points of interest (POIs) in which the text information contains all query keywords close to the query location and with a small mutual distance. The query goal of the cohesive group is to identify a group of users that are closely connected geographically and socially, whereas the query purpose of the collective spatial keyword cohesive group is to determine a pair of optimally matched POI sets and user sets that satisfy the query requirements. To address this problem, a novel type of cohesive group query mode is proposed for collective spatial keywords. Initially, the candidate POI set is obtained through a fast greedy query process. Then, the core tree structure is used to store the results of (k,c)-core decomposition to improve the efficiency of cohesive group query and ensure that the query results can satisfy the social constraints among users and the spatial constraints among POIs simultaneously. The experiments conducted on real datasets show that the proposed method is one to two orders of magnitude faster than the query efficiency of the enumeration method, and the results exhibit high query accuracy.
- 参考文献/References:
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备注/Memo
收稿日期:2022-11-11。
基金项目:国家自然科学基金面上项目（61772249）.
作者简介:孟祥福，教授，博士生导师，主要研究方向为top-k查询、时空大数据。主持国家自然科学基金项目2项，辽宁省各类基金项目4项，发表学术论文20余篇，出版学术专著2部。E-mail：marxi@126.com;赖贞祥，硕士研究生，主要研究方向为集合空间关键字查询、内聚组查询。E-mail：18642972913@163.com;崔江燕，硕士研究生，主要研究方向为图嵌入、最短路径距离预测和查询。E-mail：1315249765@qq.com
通讯作者:孟祥福. E-mail：marxi@126.com
更新日期/Last Update:
1900-01-01