A Formal-Concept-Lattice Driven Approach for Skyline Refinement

Haddache, Mohamed; Hadjali, Allel; Asayesh, Hamid

doi:10.1007/978-3-030-22999-3_47

Cited by 2 publications

(12 citation statements)

References 22 publications

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“…As it can be seen, we use the formal concepts (2) and (4). The former is initially studied in the approaches proposed in Haddache et al (2019a, b). As in Djouadi and Prade (2011), we denote the fuzzy formal concept by 〈A,B〉 where A∈LO, B∈LP, A=true{o1α1,o2α2,⋯,onαntrue} and B=true{p1β1,p2β2,⋯,pwβwtrue} where αi∈false[0,1false], βj∈false[0,1false] and when we use a formal concept with crisp extent αi∈true{0,1true}, (1≤i≤n, <...>…”

Section: Preliminaries and Problem Definitionmentioning

confidence: 99%

“…In our context, the objects correspond to the tuples of the target database and the properties represent the attributes of the database tuples. First, we substantially revise and restate the preliminary conference works done in Haddache et al (2019a, b). Solutions proposed in these studies suffer unfortunately of some serious drawbacks and are time-consuming (due the lattice structure building and scanning).…”

Section: Introductionmentioning

confidence: 99%

“…In summary, the main new contributions made in this paper cover the following points:We discuss a new method based on the fuzzy formal concept analysis, to refine the skyline S. The resulting refining process always succeeds and is a user-dependent. The methods proposed in Haddache et al (2019a, b) are of an iterative nature and allow returning a flat subset containing k skyline objects, while the solution discussed here establishes a rank-order on the skyline objects and retrieves the top−k (i.e., a discriminated subset).We develop and implement an optimized algorithm to efficiently compute the refined skyline Sref. Furthermore, we provide a complete analysis of the theoretical complexity of all the algorithms studied for the comparison purpose.We conduct a set of thorough experiments to study, analyze and compare the relevance and effectiveness of the proposed method with the approaches proposed in Haddache et al (2019a, b), the naive Papadias et al (2003) and outranking Haddache et al (2016) methods.…”

Section: Introductionmentioning

confidence: 99%

“…We discuss a new method based on the fuzzy formal concept analysis, to refine the skyline S. The resulting refining process always succeeds and is a user-dependent. The methods proposed in Haddache et al (2019a, b) are of an iterative nature and allow returning a flat subset containing k skyline objects, while the solution discussed here establishes a rank-order on the skyline objects and retrieves the top−k (i.e., a discriminated subset).…”

Section: Introductionmentioning

confidence: 99%

“…We conduct a set of thorough experiments to study, analyze and compare the relevance and effectiveness of the proposed method with the approaches proposed in Haddache et al (2019a, b), the naive Papadias et al (2003) and outranking Haddache et al (2016) methods.…”

Section: Introductionmentioning

confidence: 99%

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Skyline refinement exploiting fuzzy formal concept analysis

Haddache

Hadjali

Asayesh

2021

IJICC

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PurposeThe 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.Design/methodology/approachThe 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.FindingsAn 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.Research limitations/implicationsThe 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.Practical implicationsThe 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.Social implicationsThis work can be expected in all domains that require decision-making like hotel finder, restaurant recommender, recruitment of candidates, etc.Originality/valueThis 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.

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