Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks
Location search and recommendation have received significant attention in recent years. To protect the users' privacy, we propose and study a novel privacy-protected route-based spatial-textual location (PPRSTL) query in road networks. Given a set of locations O with the textual description, a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8668485/ |
| _version_ | 1819276486219137024 |
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| author | Hongwei Liu Yongjiao Sun Gang Wu Guoren Wang |
| author_facet | Hongwei Liu Yongjiao Sun Gang Wu Guoren Wang |
| author_sort | Hongwei Liu |
| collection | DOAJ |
| description | Location search and recommendation have received significant attention in recent years. To protect the users' privacy, we propose and study a novel privacy-protected route-based spatial-textual location (PPRSTL) query in road networks. Given a set of locations O with the textual description, a query route q with a set of query keywords to describe user's preference, the PPRSTL query finds the location with the highest spatial-textual similarity to the query route q. We believe that such type of query is very useful in many mobile applications such as location recommendation and discovery, and location-based services in general. The problem is challenging due to three reasons: (1) how to model the spatial and textual similarity practically; (2) how to constrain the search space in a comparatively small range in the spatial and textual domains, and; (3) how to protect the users' privacy when returning the query results. To overcome these challenges, we define a boolean spatial-textual measure to evaluate the similarity in the spatial and textual domains, and a two-phase search mechanism to protect users' privacy. We develop two expansion search algorithms that follow the filter-and-refinement paradigm, to compute the queries efficiently. Two pairs of upper and lower bounds are defined to prune the search space effectively. In addition, we adopt an expansion center selection method to further enhance the query efficiency. Finally, we conduct extensive experiments on real and synthetic spatial data sets to verify the performance of the developed algorithms. |
| first_indexed | 2024-12-23T23:40:59Z |
| format | Article |
| id | doaj.art-1463de2a40074c40a366d67e2dda322d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:40:59Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1463de2a40074c40a366d67e2dda322d2022-12-21T17:25:39ZengIEEEIEEE Access2169-35362019-01-017823498235710.1109/ACCESS.2019.29038988668485Privacy-Protected Route-Based Spatial-Textual Location Search in Road NetworksHongwei Liu0Yongjiao Sun1https://orcid.org/0000-0003-3373-0723Gang Wu2Guoren Wang3College of Computer Science and Engineering, Northeastern University, Shenyang, ChinaCollege of Computer Science and Engineering, Northeastern University, Shenyang, ChinaCollege of Computer Science and Engineering, Northeastern University, Shenyang, ChinaCollege of Computer Science and Engineering, Beijing Institute of Technology, Beijing, ChinaLocation search and recommendation have received significant attention in recent years. To protect the users' privacy, we propose and study a novel privacy-protected route-based spatial-textual location (PPRSTL) query in road networks. Given a set of locations O with the textual description, a query route q with a set of query keywords to describe user's preference, the PPRSTL query finds the location with the highest spatial-textual similarity to the query route q. We believe that such type of query is very useful in many mobile applications such as location recommendation and discovery, and location-based services in general. The problem is challenging due to three reasons: (1) how to model the spatial and textual similarity practically; (2) how to constrain the search space in a comparatively small range in the spatial and textual domains, and; (3) how to protect the users' privacy when returning the query results. To overcome these challenges, we define a boolean spatial-textual measure to evaluate the similarity in the spatial and textual domains, and a two-phase search mechanism to protect users' privacy. We develop two expansion search algorithms that follow the filter-and-refinement paradigm, to compute the queries efficiently. Two pairs of upper and lower bounds are defined to prune the search space effectively. In addition, we adopt an expansion center selection method to further enhance the query efficiency. Finally, we conduct extensive experiments on real and synthetic spatial data sets to verify the performance of the developed algorithms.https://ieeexplore.ieee.org/document/8668485/Privacy protectionlocation searchroutespatial-textualroad networks |
| spellingShingle | Hongwei Liu Yongjiao Sun Gang Wu Guoren Wang Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks IEEE Access Privacy protection location search route spatial-textual road networks |
| title | Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks |
| title_full | Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks |
| title_fullStr | Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks |
| title_full_unstemmed | Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks |
| title_short | Privacy-Protected Route-Based Spatial-Textual Location Search in Road Networks |
| title_sort | privacy protected route based spatial textual location search in road networks |
| topic | Privacy protection location search route spatial-textual road networks |
| url | https://ieeexplore.ieee.org/document/8668485/ |
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