{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:42:46Z","timestamp":1754156566671,"version":"3.41.2"},"reference-count":55,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T00:00:00Z","timestamp":1619654400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJICC"],"published-print":{"date-parts":[[2021,7,15]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The study of the skyline queries has received considerable attention from several database researchers since the end of 2000's. Skyline queries are an appropriate tool that can help users to make intelligent decisions in the presence of multidimensional data when different, and often contradictory criteria are to be taken into account. Based on the concept of Pareto dominance, the skyline process extracts the most interesting (not dominated in the sense of Pareto) objects from a set of data. Skyline computation methods often lead to a set with a large size which is less informative for the end users and not easy to be exploited. The purpose of this paper is to tackle this problem, known as the large size skyline problem, and propose a solution to deal with it by applying an appropriate refining process.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>The problem of the skyline refinement is formalized in the fuzzy formal concept analysis setting. Then, an ideal fuzzy formal concept is computed in the sense of some particular defined criteria. By leveraging the elements of this ideal concept, one can reduce the size of the computed Skyline.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>An appropriate and rational solution is discussed for the problem of interest. Then, a tool, named SkyRef, is developed. Rich experiments are done using this tool on both synthetic and real datasets.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title><jats:p>The authors have conducted experiments on synthetic and some real datasets to show the effectiveness of the proposed approaches. However, thorough experiments on large-scale real datasets are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title><jats:p>The tool developed SkyRef can have many domains applications that require decision-making, personalized recommendation and where the size of skyline has to be reduced. In particular, SkyRef can be used in several real-world applications such as economic, security, medicine and services.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Social implications<\/jats:title><jats:p>This work can be expected in all domains that require decision-making like hotel finder, restaurant recommender, recruitment of candidates, etc.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This study mixes two research fields artificial intelligence (i.e. formal concept analysis) and databases (i.e. skyline queries). The key elements of the solution proposed for the skyline refinement problem are borrowed from the fuzzy formal concept analysis which makes it clearer and rational, semantically speaking. On the other hand, this study opens the door for using the formal concept analysis and its extensions in solving other issues related to skyline queries, such as relaxation.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijicc-11-2020-0181","type":"journal-article","created":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T01:30:21Z","timestamp":1619659821000},"page":"333-362","source":"Crossref","is-referenced-by-count":2,"title":["Skyline refinement exploiting fuzzy formal concept analysis"],"prefix":"10.1108","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3493-2108","authenticated-orcid":false,"given":"Mohamed","family":"Haddache","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4452-1647","authenticated-orcid":false,"given":"Allel","family":"Hadjali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5168-2692","authenticated-orcid":false,"given":"Hamid","family":"Azzoune","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2021,4,29]]},"reference":[{"first-page":"321","article-title":"A linguistic quantifier-based approach for skyline refinement","year":"2013","key":"key2021071504375699800_ref001"},{"first-page":"1","article-title":"Skycover: finding range-constrained approximate skylines with bounded quality guarantees","year":"2016","key":"key2021071504375699800_ref002"},{"issue":"1","key":"key2021071504375699800_ref003","first-page":"31","article-title":"A survey on multi criteria decision making methods and its applications","volume":"1","year":"2013","journal-title":"American Journal of Information Systems"},{"first-page":"80","article-title":"Exploiting indifference for customization of partial order skylines","year":"2006","key":"key2021071504375699800_ref004"},{"first-page":"209","article-title":"User interaction support for incremental refinement of preference-based queries","year":"2007","key":"key2021071504375699800_ref005"},{"key":"key2021071504375699800_ref006","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.asoc.2018.10.013","article-title":"On fuzzy approaches for enlarging skyline query results","volume":"74","year":"2019","journal-title":"Applied Soft Computing"},{"key":"key2021071504375699800_ref007","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1002\/malq.19990450408","article-title":"Fuzzy galois connections","volume":"45","year":"1999","journal-title":"Mathematical Logic Quarterly"},{"issue":"3","key":"key2021071504375699800_ref008","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1109\/TFUZZ.2010.2041006","article-title":"Computing the lattice of all fixpoints of a fuzzy closure operator","volume":"18","year":"2010","journal-title":"IEEE Transactions on Fuzzy Systems"},{"first-page":"540","article-title":"On the use of fuzzy dominance for computing service skyline based on qos","year":"2011","key":"key2021071504375699800_ref009"},{"issue":"4","key":"key2021071504375699800_ref010","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1145\/322092.322095","article-title":"On the average number of maxima in a set of vectors and applications","volume":"25","year":"1978","journal-title":"Journal of the ACM"},{"first-page":"421","article-title":"The skyline operator","year":"2001","key":"key2021071504375699800_ref011"},{"issue":"1","key":"key2021071504375699800_ref012","first-page":"209","article-title":"The study of the l-fuzzy concept lattice","volume":"3","year":"1994","journal-title":"Mathware and Soft Computing"},{"issue":"2","key":"key2021071504375699800_ref013","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1108\/IJICC-05-2018-0060","article-title":"Universal usability evaluation by using an integrated fuzzy multi criteria decision making approach","volume":"12","year":"2019","journal-title":"Int. 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