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Danh sách kết quả tìm kiếm tài liệu từ 1 đến 6 trong 6 tài liệu phù hợp.
Tài liệu phù hợp với tiêu chí tìm kiếm:
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  • SecEDMO: Enabling Efficient Data Mining with Strong Privacy Protection in Cloud Computing

    • Tác giả: Wu, Jiahui;  Người hướng dẫn: -;  Người tham gia: Mu, Nankun; Lei, Xinyu; Le, Junqing; Zhang, Di; Liao, Xiaofeng (2019)

  • Frequent itemsets mining and association rules mining are among the top used algorithms in the area of data mining. Secure outsourcing of data mining tasks to the third-party cloud is an effective option for data owners. However, due to the untrust cloud and the distrust between data owners, the traditional algorithms which only work over plaintext should be re-considered to take security and privacy concerns into account. For example, each data owner may not be willing to disclose their own private data to others during the cooperative data mining process. The previous solutions are either not sufficiently secure or not efficient. Therefore, we propose a Secure and Efficient Data Mining Outsourcing (SecEDMO) scheme for secure outsourcing of frequent itemsets mining and association ...
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  • A Tool-Based Framework to Assess and Challenge the Responsiveness of Emergency Call Centers

    • Tác giả: Petitdemange, Eva;  Người hướng dẫn: -;  Người tham gia: Fontanili, Franck; Lamine, Elyes; Lauras, Matthieu; Okongwu, Uche (2019)

  • Emergency call centers (ECCs) are upstream of the prehospital emergency medical system and the life of many people depends on their effectiveness and responsiveness. This notwithstanding, the way their operations are organized and managed differs from one place to another. Also, depending on the number of incoming calls and available resources, they can operate differently. In the face of these heterogeneous situations, some ECCs do not always meet the expected performance levels: people still wait for too long before their call is answered. Moreover, they may have difficulties in managing an important upsurge of calls, especially in periods of crisis. Therefore, to support ECCs’ organizational improvement steps, this article aims to develop a tool-based framework that would enable ...
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  • Uncertainty based Pattern Mining for Maximizing Profit of Manufacturing Plants with List Structure

    • Tác giả: Yun, Unil;  Người hướng dẫn: -;  Người tham gia: Baek, Yoonji; Yoon, Eunchul; Fournier-Viger, Philippe (2019)

  • Products in manufacturing plants are not always manufactured without defects. The probability that commodities are produced without defects is uncertain. Uncertainty based pattern mining can discover information about a set of goods by considering the possibilities. Besides, products have different importance due to diverse characteristics of goods. Therefore, we propose a list-based pattern mining method over uncertain data considering an importance condition in this paper. The proposed method extracts commodities with large values that take into account importance of merchandise and probability that can be as non-defective products. A list structure is efficient to be created and store a database as a minimal expression. The proposed approach is able to find results more accuratel...
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  • Survey of Immersive Analytics

    • Tác giả: Fonnet, Adrien;  Người hướng dẫn: -;  Người tham gia: Prié, Yannick (2020)

  • Immersive analytics (IA) is a new term referring to the use of immersive technologies for data analysis. Yet such applications are not new, and numerous contributions have been made in the last three decades. However, no survey reviewing all these contributions is available. Here we propose a survey of IA from the early nineties until the present day, describing how rendering technologies, data, sensory mapping, and interaction means have been used to build IA systems, as well as how these systems have been evaluated. The conclusions that emerge from our analysis are that: multi-sensory aspects of IA are under-exploited, the 3DUI and VR community knowledge regarding immersive interaction is not sufficiently utilised, the IA community should focus on converging towards best practices...
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  • Mining Spatio-temporal Reachable Regions With Multiple Sources over Massive Trajectory Data

    • Tác giả: Ding, Yichen;  Người hướng dẫn: -;  Người tham gia: Zhou, Xun; Wu, Guojun; Li, Yanhua; Bao, Jie; Zheng, Yu; Luo, Jun (2020)

  • Given a set of user-specified locations and a massive trajectory dataset, the task of mining spatio-temporal reachable regions aims at finding which road segments are reachable from these locations within a given temporal period based on the historical trajectories. Determining such spatio-temporal reachable regions with high accuracy is vital for many urban applications, such as location-based recommendations and advertising. Traditional approaches to answering such queries essentially perform a distance-based range query over the given road network, which does not consider dynamic travel time at different time of day. By contrast, we propose a data-driven approach to formulate the problem as mining actual reachable regions based on a real historical trajectory dataset. Efficient a...
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  • Interactive Bike Lane Planning using Sharing Bikes' Trajectories

    • Tác giả: He, Tianfu;  Người hướng dẫn: -;  Người tham gia: Bao, Jie; Ruan, Sijie; Li, Ruiyuan; Li, Yanhua; He, Hui; Zheng, Yu (2019)

  • Cycling as a green transportation mode has been promoted by many governments all over the world. As a result, constructing effective bike lanes has become a crucial task to promote the cycling life style, as well-planned bike lanes can reduce traffic congestions and safety risks. Unfortunately, existing trajectory mining approaches for bike lane planning do not consider one or more key realistic government constraints: 1) budget limitations, 2) construction convenience, and 3) bike lane utilization. In this paper, we propose a data-driven approach to develop bike lane construction plans based on the large-scale real world bike trajectory data collected from Mobike, a station-less bike sharing system. We enforce these constraints to formulate our problem and introduce a flexible obje...
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