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1st International Conference on Intelligent Computing in Data Sciences (ICDS)

作者： Fariss, Mourad Asaidi, Hakima Bellouki, Mohamed Lab MASI FPN BP 300 Selouane 62700 Nador Morocco

Nowadays, Web Services has become one of the hot issues in the area of computer sciences, that makes an ability to collect capabilities and components in a unique interface to fulfill the user's requirements. Sometimes, two or more services can be found in available list of services;therefore, there should be a possibility for selecting the best services from discovered list which can satisfy the user's needs. The selected services should optimize the overall QoS of the composed application, while satisfying all the constraints specified by the consumer on individual QoS parameters. In this paper, we propose a contrast analysis between two skyline algorithms and evaluate them experimentally. (C) 2018 The Authors. Published by Elsevier B.V.

关键词： Web service selection skyline algorithms QoS BBS algorithm SFS algorithm

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Comparative study of skyline algorithms for selecting Web Services based on QoS

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Procedia Computer Science 2018年 127卷 408-415页

作者： Mourad Fariss Hakima Asaidi Mohamed Bellouki Laboratoire MASI FPN B.P 300 Selouane 62700 Nador Morrocco

Nowadays, Web Services has become one of the hot issues in the area of computer sciences, that makes an ability to collect capabilities and components in a unique interface to fulfill the user’s requirements. Sometimes, two or more services can be found in available list of services; therefore, there should be a possibility for selecting the best services from discovered list which can satisfy the user’s needs. The selected services should optimize the overall QoS of the composed application, while satisfying all the constraints specified by the consumer on individual QoS parameters. In this paper, we propose a contrast analysis between two skyline algorithms and evaluate them experimentally.

关键词： Web service selection skyline algorithms QoS BBS algorithm SFS algorithm

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skyline-based dissimilarity of images

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JOURNAL OF INTELLIGENT INFORMATION SYSTEMS 2019年第3期53卷 509-545页

作者： Georgiadis, Nikolaos Tiakas, Eleftherios Manolopoulos, Yannis Papadopoulos, Apostolos N. Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece Open Univ Cyprus Fac Pure Appl Sci CY-2220 Nicosia Cyprus

Large image collections are being used in many modern applications. In this paper, we aim at capturing the intrinsic dissimilarities of image descriptors in large image collections, i.e., to detect dissimilar (or else diverse) images without defining an explicit similarity or distance measure. Towards this goal, we adopt skyline processing techniques for large image databases, based on their high-dimensional descriptor vectors. The novelty of the proposed methodology lies in the use of skyline techniques empowered by state-of-the-art hashing schemes to enable effective data partitioning and indexing in secondary memory, towards supporting large image databases. The proposed approach is evaluated experimentally by using three real-world image datasets. Performance evaluation results demonstrate that images lying on the skyline have significantly different characteristics, which depend on the type of the descriptor. Thus, these skyline items may be used as seeds to apply clustering in large image databases. In addition, we observe that skyline processing using hash-based indexing structures is significantly faster than index-free skyline computation and also more efficient than skyline computation with hierarchical indexing structures. Based on our results, the proposed approach is both efficient (regarding runtime) and effective (with respect to image diversity) and therefore can be used as a base for more complex data mining tasks such as clustering.

关键词： Image databases Image descriptors skyline algorithms Hashing techniques

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skyline in Crowdsourcing with Imprecise Comparisons 21

Skyline in Crowdsourcing with Imprecise Comparisons

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30th ACM International Conference on Information and Knowledge Management (CIKM)

作者： Anagnostopoulos, Aris Fazzone, Adriano Vettraino, Giacomo Sapienza Univ Rome Rome Italy

ISBN: (纸本)9781450384469

Given an input of a set of objects each one represented as a vector of features in a feature space, the problem of finding the skyline is the problem of determining the subset of objects that are not dominated by any other input object. An example of an application is to find the best hotel(s) with respect to some features (location, price, cleanliness, etc.) The use of the crowd for solving this problem is useful when a score of items according to their features is not available. Yet the crowd can give inconsistent answers. In this paper we study the computation of the skyline when the comparisons between objects are performed by humans. We model the problem using the threshold model [1] in which the comparison of two objects may create errors/inconsistencies if the objects are close to each other. We provide algorithms for the problem and we analyze the required number of human comparisons and lower bounds. We also evaluate the effectiveness and efficiency of our algorithms using synthetic and real-world data.

关键词： Crowdsourcing human computation skyline algorithms worker models

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Detecting Intrinsic Dissimilarities in Large Image Databases through skylines 17

Detecting Intrinsic Dissimilarities in Large Image Databases...

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9th International Conference on Management of Emergent Digital EcoSystems (MEDES)

作者： Georgiadis, Nikolaos Tiakas, Eleftherios Manolopoulos, Yannis Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece

ISBN: (纸本)9781450348959

In this paper we try to detect dissimilar images in image databases without defining a similarity ranking function by capturing the intrinsic dissimilarities of image descriptor vectors. To this end, we apply the skyline operation using their multi-dimensional descriptor vectors. We implemented a number of skyline methods, combined with four hashing state-of-the-art algorithms for data partitioning to create efficient indexing to secondary memory. We compared and evaluated their results by using two real image datasets to measure the performance and the effectiveness of the implemented algorithms. Detailed results show the efficiency and effectiveness of our approach.

关键词： image databases skyline algorithms hashing methods

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