Ranking Methods for Skyline Queries

Ranking Methods for Skyline Queries | 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PDF Research Article Ranking Methods for Skyline Queries Mickaël Martin Nevot, Lotfi Lakhal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7195029/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Feb, 2026 Read the published version in Knowledge and Information Systems → Version 1 posted 19 You are reading this latest preprint version Abstract Multi-criteria decision analysis in databases has been actively studied, especially through the Skyline operator. Yet, few approaches offer a relevant comparison of Pareto optimal, or Skyline, points for high cardinality result sets. We propose to improve the dp-idp method, inspired by tf-idf, a recent approach computing a score for each Skyline point, by introducing the concept of dominance hierarchy. As dp-idp lacks efficiency and does not ensure a distinctive rank, we introduce the RankSky method, the adaptation of Google’s well-known PageRank solution, using a square stochastic matrix, a teleportation matrix, a damping factor, and then a row score eigenvector and the IPL algorithm. For the same reasons as RankSky, and also to offer directly embeddable in DBMS solution, we establish the TOPSIS based CoSky method, derived from both information research and multi-criteria analysis. CoSky automatically ponderates normalized attributes using the Gini index, then computes a score using Salton's cosine toward an ideal point. By coupling multilevel Skyline to dp-idp, RankSky or CoSky, we introduce DeepSky. Implementations of dp-idp, RankSky and CoSky are evaluated experimentally. Multiple-criteria decision analysis Skyline Information retrieval Ranking PageRank Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 16 Feb, 2026 Read the published version in Knowledge and Information Systems → Version 1 posted Editorial decision: Revision requested 10 Oct, 2025 Reviews received at journal 21 Sep, 2025 Reviews received at journal 17 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviews received at journal 31 Aug, 2025 Reviewers agreed at journal 25 Aug, 2025 Reviewers agreed at journal 22 Aug, 2025 Reviewers agreed at journal 22 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 19 Aug, 2025 Reviewers agreed at journal 17 Aug, 2025 Reviewers agreed at journal 17 Aug, 2025 Reviewers agreed at journal 17 Aug, 2025 Reviewers invited by journal 17 Aug, 2025 Editor assigned by journal 23 Jul, 2025 Submission checks completed at journal 23 Jul, 2025 First submitted to journal 23 Jul, 2025 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. 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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-7195029","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":504377362,"identity":"67ffd684-f676-4c84-8c65-70cce135263f","order_by":0,"name":"Mickaël Martin Nevot","email":"data:image/png;base64,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","orcid":"","institution":"Aix-Marseille Université","correspondingAuthor":true,"prefix":"","firstName":"Mickaël","middleName":"Martin","lastName":"Nevot","suffix":""},{"id":504377363,"identity":"9fe8987c-58c4-4354-91c1-619fe4de9863","order_by":1,"name":"Lotfi Lakhal","email":"","orcid":"","institution":"Aix-Marseille Université","correspondingAuthor":false,"prefix":"","firstName":"Lotfi","middleName":"","lastName":"Lakhal","suffix":""}],"badges":[],"createdAt":"2025-07-23 10:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7195029/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7195029/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10115-026-02684-7","type":"published","date":"2026-02-16T15:57:40+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":103251071,"identity":"340e6e8e-3aad-47c5-9db0-b7c1bcae72ce","added_by":"auto","created_at":"2026-02-23 16:03:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":737559,"visible":true,"origin":"","legend":"","description":"","filename":"RankingMethodsForSkylineQueriesKAISMickalMartinNevotEtAl.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7195029/v1_covered_86863294-2d12-47ab-8759-33190eb8b877.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ranking Methods for Skyline Queries","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"knowledge-and-information-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"kais","sideBox":"Learn more about [Knowledge and Information Systems](http://link.springer.com/journal/10115)","snPcode":"10115","submissionUrl":"https://submission.nature.com/new-submission/10115/3","title":"Knowledge and Information Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Multiple-criteria decision analysis, Skyline, Information retrieval, Ranking, PageRank","lastPublishedDoi":"10.21203/rs.3.rs-7195029/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7195029/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Multi-criteria decision analysis in databases has been actively studied, especially through the Skyline operator. 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