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2016 IEEE 32nd International Conference on Data Engineering Workshops (ICDEW)

16-20 May 2016

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Displaying Results 1 - 25 of 57
  • [Label art]

    Publication Year: 2016, Page(s): 1
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  • Welcome

    Publication Year: 2016, Page(s): 1
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  • Hub page

    Publication Year: 2016, Page(s): 1
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  • Workshops list

    Publication Year: 2016, Page(s): 1
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  • Table of contents

    Publication Year: 2016, Page(s):1 - 6
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  • Author index

    Publication Year: 2016, Page(s):1 - 4
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  • Detailed author index

    Publication Year: 2016, Page(s):1 - 27
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  • The end of indexes

    Publication Year: 2016, Page(s): 1
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  • About CP

    Publication Year: 2016, Page(s): 1
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  • Frequently asked questions

    Publication Year: 2016, Page(s):1 - 6
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  • [Workshop on cloud data management (CloudDM) - Front matter]

    Publication Year: 2016, Page(s):1 - 4
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  • Efficient skew handling in online aggregation in the cloud

    Publication Year: 2016, Page(s):5 - 11
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (259 KB) | HTML iconHTML

    As the development of social network, mobile Internet, etc., an increasing amount of data are being generated, which beyonds the processing ability of traditional data management tools. In many real-life applications, users can accept approximate answers accompanied by accuracy guarantees. One of the most commonly used approaches is online aggregation. Online aggregation responds aggregation queri... View full abstract»

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  • High variety cloud databases

    Publication Year: 2016, Page(s):12 - 19
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (223 KB) | HTML iconHTML

    Big Data is colloquially described in terms of the three Vs: Volume, Velocity, and Variety. Volume and velocity receive a disproportionate amount of research attention, however, variety is frequently cited by practitioners as the Big Data problem that “keeps them up at night” - the problem that resists direct attacks in terms of new algorithms, systems, and approaches. We find that t... View full abstract»

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  • A comparison of Flashcache with IQ-Twemcached

    Publication Year: 2016, Page(s):20 - 26
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    Person-to-person cloud service providers such as Facebook use Host-side (HsC) and Application-side (AsC) caches to enhance performance. Using Facebook's Flashcache as the representative of HsC and IQ-Twemcached as the representative of AsC, this study quantifies their tradeoffs using both a read-heavy and a write-heavy workload. Obtained results show Flashcache provides significant benefit for I/O... View full abstract»

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  • Workload management for cloud databases via machine learning

    Publication Year: 2016, Page(s):27 - 30
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (554 KB) | HTML iconHTML

    As elastic IaaS clouds continue to become more cost efficient than on-site datacenters, a wide range of data management applications are migrating to pay-as-you-go cloud computing resources. These diverse applications come with an equally diverse set of performance goals, resource demands, and budget constraints. While existing research has tackled individual tasks such as query placement, schedul... View full abstract»

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  • Aggressive buffer pool warm-up after restart in SQL Server

    Publication Year: 2016, Page(s):31 - 38
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (949 KB) | HTML iconHTML

    In many settings, a database server has to be restarted either in response to a failure event, or in response to an operational decision such as moving a database service from one machine to another. However, such restarts pose a potential performance problem as the new database server starts off with a cold buffer pool. As a result, the database application experiences a dramatic reduction in per... View full abstract»

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  • IncReStore: Incremental computation of mapreduce workflows

    Publication Year: 2016, Page(s):39 - 46
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (524 KB) | HTML iconHTML

    Many applications in various industrial and research areas analyze large continuously evolving data. Big data analytics platforms such as MapReduce focus on distributed batch processing, and therefore, a query needs to be re-executed every time its input data evolve. In this paper, we present IncReStore, a system that incrementally computes queries on fast growing datasets by materializing query o... View full abstract»

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  • [Health data management & mining (HDMM) workshop - front matter]

    Publication Year: 2016, Page(s):47 - 49
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  • A smartphone app provides preventive care for the elderly with dementia

    Publication Year: 2016, Page(s):50 - 53
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (385 KB) | HTML iconHTML

    This paper reports an ongoing project of preventive care for elder citizens with dementia by using a smartphone app. Identification of early signs of the disease is critical for prevention and treatment. We focus on an early sign of dementia that the elderly often show in daily life when they operate electronic devices. We describe a design of a smartphone app that detects the specific sign and sc... View full abstract»

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  • Air quality assessment from social media and structured data: Pollutants and health impacts in urban planning

    Publication Year: 2016, Page(s):54 - 59
    Cited by:  Papers (1)
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    This paper describes our work on mining pollutant data to assess air quality in urban areas. Notable aspects of this work are that we mine social media and structured data in a domain-specific context, incorporate commonsense knowledge in mining media opinions and focus on the urban planning domain in a multicity environment. The results of mining are useful for predictive analysis in urbanization... View full abstract»

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  • Data mining for better healthcare: A path towards automated data analysis?

    Publication Year: 2016, Page(s):60 - 63
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (266 KB) | HTML iconHTML

    In today's world, large volumes of medical data are being continuously generated, but their value is severely undermined by our inability to translate them into knowledge and, ultimately, actions. Data mining techniques allow the extraction of previously unknown interesting patterns from large datasets, but their complexity limits their practical diffusion. Data-driven analysis is a multi-step pro... View full abstract»

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  • Timeline and episode-structured clinical data: Pre-processing for Data Mining and analytics

    Publication Year: 2016, Page(s):64 - 67
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (100 KB) | HTML iconHTML

    Data Mining has been used in the healthcare domain for diagnosis and treatment analysis, resource management and fraud detection. It brings a set of tools and techniques that can be applied to large-scale patient data to discover underlying patterns and provide healthcare professionals an additional source of knowledge for making decisions. The Southampton Breast Cancer Data System (SBCDS) contain... View full abstract»

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  • Mining internet media for monitoring changes of public emotions about infectious diseases

    Publication Year: 2016, Page(s):68 - 70
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (227 KB) | HTML iconHTML

    The Internet encompasses websites, email, social media, and Internet-based television. Given the widespread use of networked computers and mobile devices, it has become possible to monitor the behavior of Internet users by examining their access logs and queries. Based on large-scale web and text mining of Internet media articles and associated user comments, we propose a framework to rapidly moni... View full abstract»

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  • Visual exploration and cohort identification of acute patient histories aggregated from heterogeneous sources

    Publication Year: 2016, Page(s):71 - 77
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (507 KB) | HTML iconHTML

    How can we use information visualization to support retrospective, exploratory analysis of collections of histories for patients admitted to acute care? This paper describes a novel design for visual cohort identification and exploration. We have developed a tool that integrates multiple, heterogeneous clinical data sources and allows alignment, querying and abstraction in a common workbench. This... View full abstract»

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  • A sensor network query processing system for healthcare data acquisition in Dr. M

    Publication Year: 2016, Page(s):78 - 83
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (593 KB) | HTML iconHTML

    In mobile healthcare monitoring services with wearable sensor devices and mobile communications networks, data acquisition is an important issue for the design and implementation of various healthcare application services. In this paper, we present an efficient healthcare data acquisition apparatus by accommodating the notion of query language and processing functions of the sensor network databas... View full abstract»

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