• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.207-218
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• 2012

In recent years, the skyline query paradigm has been established as a reliable method for database query personalization. While early efficiency problems have been solved by sophisticated algorithms and advanced indexing, new challenges in skyline retrieval effectiveness continuously arise. In particular, the rise of the Semantic Web and linked open data leads to personalization issues where skyline queries cannot be applied easily. We addressed the special challenges presented by linked open data in previous work; and now further extend this work, with a heuristic workflow to boost efficiency. This is necessary; because the new view on linked open data dominance has serious implications for the efficiency of the actual skyline computation, since transitivity of the dominance relationships is no longer granted. Therefore, our contributions in this paper can be summarized as: we present an intuitive skyline query paradigm to deal with linked open data; we provide an effective dominance definition, and establish its theoretical properties; we develop innovative skyline algorithms to deal with the resulting challenges; and we design efficient heuristics for the case of predicate equivalences that may often happen in linked open data. We extensively evaluate our new algorithms with respect to performance, and the enriched skyline semantics.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.314-320
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• 2009

Skyline queries have recently received considerable attention in the searching services. The skyline contains interesting objects that are not dominated by any other objects on all dimensions. Many related works have processed a skyline on static data or on moving objects in Euclidean space. However, this paper assumes that the point of a skyline query continuously moves in road networks. We propose a new method that efficiently processes continuous skyline queries in road networks through pre-computed shortest range data of objects. Our experiments show that the proposed method is about 100 times faster than previous methods in terms of query processing time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1931-1953
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• 2017

The reverse skyline query plays an important role in information searching applications. This paper deals with continuous reverse skyline queries in sensor networks, which retrieves reverse skylines as well as the set of nodes that reported them for continuous sampling epochs. Designing an energy-efficient approach to answer continuous reverse skyline queries is non-trivial because the reverse skyline query is not decomposable and a huge number of unqualified nodes need to report their sensor readings. In this paper, we develop a new algorithm that avoids transmission of updates from nodes that cannot influence the reverse skyline. We propose a data mapping scheme to estimate sensor readings and determine their dominance relationships without having to know the true values. We also theoretically analyze the properties for reverse skyline computation, and propose efficient pruning techniques while guaranteeing the correctness of the answer. An extensive experimental evaluation demonstrates the efficiency of our approach.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.70-83
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• 2007

Most of works for skyline queries have focused on static data objects. With the advance in mobile applications, however, the need of continuous skyline queries for moving objects has been increasing. To process continuous skyline queries, the 4-phased decision method of skyline regions has been proposed recently. However, it is not feasible for a large number of data because of the high cost of computing skyline regions. To solve this problem, this paper first provides a theoretical analysis of the 4-phased decision method. Then we propose a progressive decision method of skyline regions for the 4-phased decision method, which consists of a distance-based pruning and an extent shrinking of region decision lines. The proposed method can efficiently reduce the cost of the decision of skyline region in the 4-phased decision method. This paper also presents the experimental results to show the effectiveness of the proposed method.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.165-179
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• 2010

Recently, the processing of data streams such as stock quotes, buy-sell orders, and billing records becomes more important in e-Business environments. Especially, the use of skyline queries over data streams is rapidly increasing to support multiple criteria decision making. Given a set of multi-dimensional tuples, a skyline query retrieves a set of tuples which are not dominated by other tuples. Although there has been much work on processing skyline queries over static datasets, there has been relatively less work on processing multiple skyline queries over data streams. In this paper, we propose an efficient method for processing multiple continuous skyline queries over data streams. The proposed method efficiently identifies which tuple is a skyline tuple of which query, resulting in a lower cost of processing multiple skyline queries. Through performance evaluation, we show the performance advantage of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.35-40
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• 2010

Skyline extraction in mountainous images which has been used for navigation of vehicles or micro unmanned air vehicles is very hard to implement because of the complexity of skyline shapes, occlusions by environments, dfficulties to detect precise edges and noises in an image. In spite of these difficulties, skyline extraction is avery important theme that can be applied to the various fields of unmanned vehicles applications. In this paper, we developed a robust skyline extraction algorithm using two-scale canny edge images, topological information and location of the skyline in an image. Two-scale canny edge images are composed of High Scale Canny edge image that satisfies good localization criterion and Low Scale Canny edge image that satisfies good detection criterion. By applying each image to the proper steps of the algorithm, we could obtain good performance to extract skyline in images under complex environments. The performance of the proposed algorithm is proved by experimental results using various images and compared with an existing method.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1591-1600
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• 2011

The skyline of a multidimensional data set is the maximal subset whose elements are not dominated by other elements of the set. Skyline computation is considered to be very useful for a decision making system that deals with multidimensional data analyses. Recently, a great deal of interests has been shown to improve the performance of skyline computation algorithms. In order to speedup, the number of comparisons between data elements should be reduced. In this paper, we propose a filter lining scheme to accomplish such objectives. The scheme divides the multidimensional data space into angle-based partitions, and places a filter for each partition, and then connects them together in order to establish the final filter line. The filter line can be used to eliminate data, that are not part of the skyline, from the original data set in the preprocessing stage. The filter line is adaptively improved during the data scanning stage. In addition, skylines are computed for each remaining data partition, and are then merged to form the final skyline. Our scheme is an improvement of the previously reported simple preprocessing scheme using simple filters. The performance of the scheme is shown by experiments.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.313-316
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• 2011

The skyline of a multi-dimensional data set is a subset that consists of the data that are not dominated by other members of the set. Skyline computation can be very useful for decision making for multi-dimensional data set. However, in case that the skyline is very large, it may not be much useful for decision making. In this paper, we propose an algorithm for computing a part of the skyline considering location restrictions that the user provides, such as origin movement, degree ranges and/or distances from the origin. The algorithm eliminates noncandidate data rapidly, and returns in order the skyline points that satisfy the user's requests. We show that the algorithm is efficient by experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1380-1381
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• 2012

인터넷이 발달함에 따라 데이터가 방대해지고 더욱 이질적인 특성을 가지게 되었다. 따라서 이질적이고 대용량 데이터에서의 빠른 검색이 중요시되고 있다. 또한, 다중 릴레이션 환경에서의 사용자 질의가 증가함에 따라 다중 릴레이션에서의 Skyline 연산의 필요성이 증가하고 있다. 본 논문에서는 다중릴레이션 환경에서의 Skyline 연산의 기존 연구들을 소개하며 문제점을 분석하고 해결책을 간략하게 제시한다.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.30-42
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• 2015

In this paper, we propose a new skyline query processing scheme to enhance accuracy of query processing and communication cost in mobile P2P environments. The proposed scheme consists of three stages such as the pre-skyline processing, the query transmission range extension policy, and the continuous skyline query processing. In the pre-skyline processing, a peer selects the candidate filtering objects who have the potential to be selected. By doing so, the proposed scheme reduces the filtering cost when processing the query. In the query transmission range extension policy, we have improved the accuracy by extending the query transmission range. In addition, it can handle continuous skyline query by performing the monitoring after the first skyline query processing. In order to show the superiority of the proposed method, we compare it with the existing schemes through performance evaluation. As a result, it was shown that the proposed scheme outperforms the existing schemes.