Computing Skyline from Evidential Data

Elmi, Sayda; Benouaret, Karim; Hadjali, Allel; Tobji, Mohamed Anis Bach; Yaghlane, Boutheina Ben

doi:10.1007/978-3-319-11508-5_13

Cited by 16 publications

(2 citation statements)

References 28 publications

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“…This model opens up the way for further researches on querying possible worlds' model to validate existing querying methods based on the compact form with the aim of proving the strong representation system relative to evidential databases.…”

Section: Discussionmentioning

confidence: 99%

Modeling evidential databases as possible worlds

Bousnina

Tobji

Chebbah

et al. 2018

Int. J. Intell. Syst.

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This paper is about modeling a possible worlds' form of imperfect databases, where imperfection is handled with the evidence theory. The possible worlds' form is already developed for other types of imperfect databases such as probabilistic and possibilistic databases. Such a form is essential to prove that a compact form querying method is a strong representation system. For the same aim, we propose in this article an extended model of possible worlds's form treating the tuple‐level uncertainty in addition to the attribute‐level uncertainty.

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Section: Discussionmentioning

confidence: 99%

Modeling evidential databases as possible worlds

Bousnina

Tobji

Chebbah

et al. 2018

Int. J. Intell. Syst.

Self Cite

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“…The Skyline module provides a Skyline query as a type of decision support query in which the user specifies interests and the system offers non‐dominated solutions (routes) to the user. A solution S i is dominated to other solution S j , if S i is better than or equal to S j in all factors (dimensions) and better in at least one factor (dimension) (Elmi et al ).…”

Section: Enriching Road Segments Based On Multi‐domain Uggcmentioning

confidence: 99%

Multi‐Domain User‐Generated Content Based Model to Enrich Road Network Data for Multi‐Criteria Route Planning

Khoshamooz

Taleai

2017

Geographical Analysis

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By utilizing today's web‐based technologies, people can act as sensors and share their perceptions, emotions and observations in a variety of data forms, such as images, videos, texts, Global Positioning System (GPS) trajectories and maps. These forms are collectively called user‐generated content (UGC). These data are in different domains and have a multi‐modality nature. Although recent efforts have probed the acquisition of local knowledge by using single‐domain UGC data in specific applications, such efforts have not thus far presented a model considering multi‐domain UGC specifically to enrich road network data. This article aims at presenting such a model wherein, with the help of each data domain of UGC, one aspect of people knowledge about the road segment is obtained. These different aspects of knowledge are integrated using a Skyline operator to support multi‐criteria route finding. We name this model ERSBU (enriching road segments based on UGC). In ERSBU, road segments are basic spatial units, and their subjective properties have been extracted by using available UGC. The scenic score for each road segment was computed by using geo‐tagged Panoramio photos. The accessibility level of each road segment to different facilities was calculated based on data captured from Wikimapia and OpenStreetMap. Moreover, for measuring the movement popularity of each road segment, Wikiloc and Everytrail GPS trajectories were utilized. For the implementation of the ERSBU model, Tehran region 6 was considered the case study area. The Evaluation of the results proved that road segments that achieved a high score based on knowledge extracted from UGC also mostly gained top scores by analyzing traditional maps. ERSBU allows users to accomplish more‐qualitative path finding by considering the multi‐view characteristics of road segments.

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