Collective spatial keyword search on activity trajectories

Song, Xiaozhao; Xu, Jiajie; Zhou, Rui; Liu, Chengfei; Zheng, Kai; Falkner, Nickolas

doi:10.1007/s10707-019-00358-x

Cited by 22 publications

(9 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first aspect compares the effect of the number of query positive keywords on the efficiency of different algorithms; the second aspect compares the effect of the number of query rejection keywords on the efficiency of different algorithms; the third aspect compares the accuracy of different algorithms executing results on different datasets; the fourth aspect compares the output probability of different results under different privacy budgets to judge the algorithm usability; and the fifth aspect compares the impact of different privacy-preserving algorithms on the accuracy of the result data at the time of publication. The methods that are compared with the proposed method in this paper are the SW algorithm [15] and the PQ algorithm [29].…”

Section: Experiments Analysismentioning

confidence: 99%

Research on Approximate Spatial Keyword Group Queries Based on Differential Privacy and Exclusion Preferences in Road Networks

Zhang,

Li,

2023

IJGI

View full text Add to dashboard Cite

A new spatial keyword group query method is proposed in this paper to address the existing issue of user privacy leakage and exclusion of preferences in road networks. The proposed query method is based on the IGgram-tree index and minimum hash set. To deal with this problem effectively, this paper proposes a query method based on the IGgram-tree index and minimum hash set. The IGgram-tree index is proposed for the first time to deal with the approximate keyword query problem in the road network. This index significantly improves the efficiency of calculating the road network distance and querying approximate keywords. Considering that spatial keyword group queries are caused by NP-hard problems with high time complexity, this paper proposes a data structure that uses the minimum hash set, which can efficiently search for the result set. To address the problem that the traditional spatial keyword group query does not consider user privacy leakage and the limitations of existing privacy protection techniques, this method proposes a differential privacy-based allocation method to better protect the privacy of data. The theoretical study and experimental analysis show that the proposed method can better handle the approximate spatial keyword group query problem based on its use of differential privacy and exclusion preferences in road networks.

show abstract

Section: Experiments Analysismentioning

confidence: 99%

Research on Approximate Spatial Keyword Group Queries Based on Differential Privacy and Exclusion Preferences in Road Networks

Zhang,

Li,

2023

IJGI

View full text Add to dashboard Cite

show abstract

“…Wu et al [225] annotate location records with keywords extracted from geo-referenced social media data using Kernel Density Estimation. The querying of trajectories enhanced with keyword-like events, termed activity trajectories, has also been studied [190,278]. Event-oriented technologies [109,110,125,126,224,239] annotate trajectory points or segments with event labels to form sequences of application-specific events.…”

Section: Data Integration (Di)mentioning

confidence: 99%

Spatial Data Quality in the Internet of Things: Management, Exploitation, and Prospects

Jensen

et al. 2022

ACM Comput. Surv.

View full text Add to dashboard Cite

With the continued deployment of the Internet of Things (IoT) , increasing volumes of devices are being deployed that emit massive spatially referenced data. Due in part to the dynamic, decentralized, and heterogeneous architecture of the IoT, the varying and often low quality of spatial IoT data (SID) presents challenges to applications built on top of this data. This survey aims to provide unique insight to practitioners who intend to develop IoT-enabled applications and to researchers who wish to conduct research that relates to data quality in the IoT setting. The survey offers an inventory analysis of major data quality dimensions in SID and covers significant data characteristics and associated quality considerations. The survey summarizes data quality related technologies from both task and technique perspectives. Organizing the technologies from the task perspective, it covers recent progress in SID quality management, encompassing location refinement, uncertainty elimination, outlier removal, fault correction, data integration, and data reduction; and it covers low-quality SID exploitation, encompassing querying, analysis, and decision-making techniques. Finally, the survey covers emerging trends and open issues concerning the quality of SID.

show abstract

“…Some other studies on spatial keyword queries focus on finding an object set as a solution. Among them, there exist works [4], [21], [3], [7], [8], [26] studying the collective spatial keyword queries (CoSKQ). Cao et al [4], [3] studied the CoSKQ problem and proposed exact and approximation algorithms for several distance functions, e.g., dist M axSum .…”

Section: Related Workmentioning

confidence: 99%

“…Xu et al [33] studied the moving CoSKQ problem and proposed both exact and approximation algorithms for the problem. Song et al [26] studied CoSKQ problem on activity trajectories and proposed an index structure and a search algorithm for the problem.…”

Section: Related Workmentioning

confidence: 99%

Cost-Aware and Distance-Constrained Collective Spatial Keyword Query

Chan¹,

Liu²,

Long³

et al. 2021

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

With the proliferation of location-based services, geo-textual data is becoming ubiquitous. Objects involved in geo-textual data include geospatial locations, textual descriptions or keywords, and various attributes (e.g., a point-of-interest has its expenses and users' ratings). Many types of spatial keyword queries have been proposed on geo-textual data. Among them, one prominent type is to find, for a query consisting of a query location and some query keywords, a set of multiple objects such that the objects in the set collectively cover all the query keywords and the object set is of good quality according to some criteria. Existing studies define the criteria either based on the geospatial information of the objects solely or simply treat the geospatial information and the attribute information of the objects together without differentiation though they may have different semantics and scales. As a result, they cannot provide users flexibility to express finer grained preferences on the objects. In this paper, we propose a new criterion which is to find a set of objects where the distance (defined based on the geospatial information) is at most a threshold specified by users and the cost (defined based on the attribute information) is optimized. We develop a suite of two algorithms including an exact algorithm and an approximation algorithm with provable guarantees for the problem. We conducted extensive experiments on real datasets which verified the efficiency and effectiveness of proposed algorithms.

show abstract

Collective spatial keyword search on activity trajectories

Cited by 22 publications

References 33 publications

Research on Approximate Spatial Keyword Group Queries Based on Differential Privacy and Exclusion Preferences in Road Networks

Research on Approximate Spatial Keyword Group Queries Based on Differential Privacy and Exclusion Preferences in Road Networks

Spatial Data Quality in the Internet of Things: Management, Exploitation, and Prospects

Cost-Aware and Distance-Constrained Collective Spatial Keyword Query

Contact Info

Product

Resources

About