Top-k Spatial Keyword Query Based on Reachability

Top-k Spatial Keyword Query Based on Reachability | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Top- k Spatial Keyword Query Based on Reachability Yanhong Li, Jiayu Ren, Changyin Luo, Yu Feng, Xiaokun Du, Jianjun Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1573042/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Spatial keyword query (SKQ) is a research hotspot in the field of spatio-temporal databases. The spatial proximity and text similarity between objects and the query are considered during query processing. In order to better meet the personal-ized needs of users and improve the accuracy and real-time of spatial keyword query results, we propose the Top-k spatial keyword query based on reachability (RSKQ). Such query returns the k best objects that satisfy the reachability and query keyword constraints according to a comprehensive score, which considers the spatial proximity, text similarity, and accessibility between the query and the object. Firstly, an efficient index called SRTR-tree is proposed, which can intelligently organize road network structure information, keywords and location information of spatio-textual objects, and vehicle trajectory information. Moreover , several pruning techniques are designed to prune massive objects irrelevant to the query according to accessibility, spatial proximity, and textual similarity, so as to speed up query processing. Based on the SRTR-tree and pruning strategies, a non-trivial basic algorithm is proposed to process RSKQ queries. In addition, we introduce a more efficient optimized algorithm to improve the efficiency of query processing. Finally, a series of experimental evaluations are carried out to show the effectiveness of our methods. Reachability Spatial keyword query Road network Trajectory data Full Text Additional Declarations No competing interests reported. Supplementary Files WWWJ.rar Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1573042","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":100520273,"identity":"00d3d311-cc17-4395-9b0c-bc5acdfe168c","order_by":0,"name":"Yanhong Li","email":"","orcid":"","institution":"South-Central Minzu University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yanhong","middleName":"","lastName":"Li","suffix":""},{"id":100520274,"identity":"b603f060-3914-4d89-b206-cdc602d6c9f9","order_by":1,"name":"Jiayu Ren","email":"","orcid":"","institution":"South-Central Minzu 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The spatial proximity and text similarity between objects and the query are considered during query processing. In order to better meet the personal-ized needs of users and improve the accuracy and real-time of spatial keyword query results, we propose the Top-k spatial keyword query based on reachability (RSKQ). Such query returns the k best objects that satisfy the reachability and query keyword constraints according to a comprehensive score, which considers the spatial proximity, text similarity, and accessibility between the query and the object. Firstly, an efficient index called SRTR-tree is proposed, which can intelligently organize road network structure information, keywords and location information of spatio-textual objects, and vehicle trajectory information. Moreover , several pruning techniques are designed to prune massive objects irrelevant to the query according to accessibility, spatial proximity, and textual similarity, so as to speed up query processing. Based on the SRTR-tree and pruning strategies, a non-trivial basic algorithm is proposed to process RSKQ queries. In addition, we introduce a more efficient optimized algorithm to improve the efficiency of query processing. 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