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2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)

1-6 March 2010

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  • [CD label]

    Publication Year: 2010, Page(s): 1
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  • Withe Label

    Publication Year: 2010, Page(s): 1
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  • Welcome

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  • [Front and back cover]

    Publication Year: 2010, Page(s):c1 - c4
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  • Hub page

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  • Session list

    Publication Year: 2010, Page(s): 1
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  • Table of contents

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  • Author index

    Publication Year: 2010, Page(s):1 - 12
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  • Detailed author index

    Publication Year: 2010, Page(s):1 - 67
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  • The end of indexes

    Publication Year: 2010, Page(s): 1
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  • [PDF Reader FAQ and support]

    Publication Year: 2010, Page(s): 1
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  • [PDF Reader FAQ and support]

    Publication Year: 2010, Page(s):1 - 5
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  • [Title page]

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  • Program chairs and general chairs

    Publication Year: 2010, Page(s):1 - 3
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  • Organizing Committee

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  • Program Committee

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  • Program Committee honors

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  • Bronze sponsors

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  • Program book

    Publication Year: 2010, Page(s):1 - 122
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  • Large scale data warehousing: Trends and observations

    Publication Year: 2010, Page(s): 1
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    Summary form only given. How large are data warehouses? How fast are they growing? How big are they going to get? What is driving their growth? Why is all this data of value in commercial enterprises? What can we say about how these large data warehouses are being used? What are some key challenges ahead? In this talk, Richard Winter will share his views and observations concerning these questions... View full abstract»

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  • DBMS: Lessons from the first 50 years, speculations for the next 50

    Publication Year: 2010, Page(s): 2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (27 KB)

    Some of the major themes in DBMS research appeared in the computer science literature as early as 50 years ago. The community has had a very productive time over the past 50 years exploring these themes, in the process contributing to a major software industry and creating a large and vibrant research community. I will give a subjective and probably highly biased view of these themes and why they ... View full abstract»

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  • How new is the cloud?

    Publication Year: 2010, Page(s): 3
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (52 KB)

    Summary form only given. Cloud computing has been identified by Gartner as one of the ten most disruptive technologies for the next decade. It has made many promises and the first products have appeared on the market place and are rapidly gaining adoption. Time to step back a bit. This talk first gives an overview of the promises made by cloud computing. Which promises really matter? Which promise... View full abstract»

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  • K nearest neighbor queries and kNN-Joins in large relational databases (almost) for free

    Publication Year: 2010, Page(s):4 - 15
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (298 KB) | HTML iconHTML

    Finding the k nearest neighbors (kNN) of a query point, or a set of query points (kNN-Join) are fundamental problems in many application domains. Many previous efforts to solve these problems focused on spatial databases or stand-alone systems, where changes to the database engine may be required, which may limit their application on large data sets that are stored in a relational database managem... View full abstract»

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  • Quantile-based KNN over multi-valued objects

    Publication Year: 2010, Page(s):16 - 27
    Cited by:  Papers (4)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (268 KB) | HTML iconHTML

    K Nearest Neighbor search has many applications including data mining, multi-media, image processing, and monitoring moving objects. In this paper, we study the problem of KNN over multi-valued objects. We aim to provide effective and efficient techniques to identify KNN sensitive to relative distributions of objects.We propose to use quantiles to summarize relative-distribution-sensitive K neares... View full abstract»

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  • Efficient rank based KNN query processing over uncertain data

    Publication Year: 2010, Page(s):28 - 39
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (337 KB) | HTML iconHTML

    Uncertain data are inherent in many applications such as environmental surveillance and quantitative economics research. As an important problem in many applications, KNN query has been extensively investigated in the literature. In this paper, we study the problem of processing rank based KNN query against uncertain data. Besides applying the expected rank semantic to compute KNN, we also introdu... View full abstract»

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