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2016 IEEE 32nd International Conference on Data Engineering (ICDE)

16-20 May 2016

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  • [USB label art]

    Publication Year: 2016, Page(s): 1
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  • [USB welcome]

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

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

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

    Publication Year: 2016, Page(s):1 - 27
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  • Brief author index

    Publication Year: 2016, Page(s):1 - 17
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  • Detailed author index

    Publication Year: 2016, Page(s):1 - 89
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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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  • Message from the ICDE 2016 Program Committee and general chairs

    Publication Year: 2016, Page(s):i - ii
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  • ICDE 2016 committees

    Publication Year: 2016, Page(s): iii
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  • Program Committee

    Publication Year: 2016, Page(s):iv - x
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  • Distance-aware influence maximization in geo-social network

    Publication Year: 2016, Page(s):1 - 12
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1840 KB) | HTML iconHTML

    Influence maximization is a key problem in viral marketing. Given a social network G and a positive integer k, it aims to identify a seed set of k nodes in G that can maximize the expected influence spread in a certain propagation model. With the proliferation of geo-social networks, location-aware product promotion is becoming more necessary in real applications. However, the importance of the di... View full abstract»

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  • Topical influence modeling via topic-level interests and interactions on social curation services

    Publication Year: 2016, Page(s):13 - 24
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (754 KB) | HTML iconHTML

    Social curation services are emerging social media platforms that enable users to curate their contents according to the topic and express their interests at the topic level by following curated collections of other users' contents rather than the users themselves. The topic-level information revealed through this new feature far exceeds what existing methods solicit from the traditional social ne... View full abstract»

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  • BlackHole: Robust community detection inspired by graph drawing

    Publication Year: 2016, Page(s):25 - 36
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (693 KB) | HTML iconHTML

    With regard to social network analysis, we concentrate on two widely-accepted building blocks: community detection and graph drawing. Although community detection and graph drawing have been studied separately, they have a great commonality, which means that it is possible to advance one field using the techniques of the other. In this paper, we propose a novel community detection algorithm for un... View full abstract»

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  • Revenue maximization by viral marketing: A social network host's perspective

    Publication Year: 2016, Page(s):37 - 48
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (427 KB) | HTML iconHTML

    We study the novel problem of revenue maximization of a social network host that sells viral marketing campaigns to multiple competing campaigners. Each client campaigner informs the social network host about her target users in the network, as well as how much money she is willing to pay to the host if one of her target users buys her product. The social network host, in turn, assigns a set of se... View full abstract»

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  • Online mobile Micro-Task Allocation in spatial crowdsourcing

    Publication Year: 2016, Page(s):49 - 60
    Cited by:  Papers (16)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (510 KB) | HTML iconHTML

    With the rapid development of smartphones, spatial crowdsourcing platforms are getting popular. A foundational research of spatial crowdsourcing is to allocate micro-tasks to suitable crowd workers. Most existing studies focus on offline scenarios, where all the spatiotemporal information of micro-tasks and crowd workers is given. However, they are impractical since micro-tasks and crowd workers i... View full abstract»

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  • Crowdsourced POI labelling: Location-aware result inference and Task Assignment

    Publication Year: 2016, Page(s):61 - 72
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (609 KB) | HTML iconHTML

    Identifying the labels of points of interest (POIs), aka POI labelling, provides significant benefits in location-based services. However, the quality of raw labels manually added by users or generated by artificial algorithms cannot be guaranteed. Such low-quality labels decrease the usability and result in bad user experiences. In this paper, by observing that crowdsourcing is a best-fit for com... View full abstract»

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  • Mutual benefit aware task assignment in a bipartite labor market

    Publication Year: 2016, Page(s):73 - 84
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (907 KB) | HTML iconHTML

    As one of the three major steps (question design, task assignment, answer aggregation) in crowdsourcing, task assignment directly affects the quality of the crowdsourcing result. A good assignment will not only improve the answers' quality, but also boost the workers' willingness to participate. Although a lot of works have been made to produce better assignment, most of them neglected one of its ... View full abstract»

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  • Computing Connected Components with linear communication cost in pregel-like systems

    Publication Year: 2016, Page(s):85 - 96
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (793 KB) | HTML iconHTML

    The paper studies two fundamental problems in graph analytics: computing Connected Components (CCs) and computing BiConnected Components (BCCs) of a graph. With the recent advent of Big Data, developing effcient distributed algorithms for computing CCs and BCCs of a big graph has received increasing interests. As with the existing research efforts, in this paper we focus on the Pregel programming ... View full abstract»

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  • VColor: A practical vertex-cut based approach for coloring large graphs

    Publication Year: 2016, Page(s):97 - 108
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (322 KB) | HTML iconHTML

    Graph coloring is a fundamental NP-hard problem in graph theory. It has a wide range of real applications, such as Operations Research, Communication Network, Computational Biology and Compiler Optimization. Notable efforts have been spent on designing its approximation algorithms. Halldrsson proposed the algorithm (denoted as SampleIS) with the current best known approximation ratio. However, its... View full abstract»

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  • Compressing graphs by grammars

    Publication Year: 2016, Page(s):109 - 120
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1201 KB) | HTML iconHTML

    We present a new graph compressor that detects repeating substructures and represents them by grammar rules. We show that for a large number of graphs the compressor obtains smaller representations than other approaches. For RDF graphs and version graphs it outperforms the best known previous methods. Specific queries such as reachability between two nodes, can be evaluated in linear time over the... View full abstract»

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  • Planar: Parallel lightweight architecture-aware adaptive graph repartitioning

    Publication Year: 2016, Page(s):121 - 132
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (533 KB) | HTML iconHTML

    Graph partitioning is an essential preprocessing step in distributed graph computation and scientific simulations. Existing well-studied graph partitioners are designed for static graphs, but real-world graphs, such as social networks and Web networks, keep changing dynamically. In fact, the communication and computation patterns of some graph algorithms may vary significantly, even across their d... View full abstract»

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  • I/O efficient Core Graph Decomposition at web scale

    Publication Year: 2016, Page(s):133 - 144
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (357 KB) | HTML iconHTML

    Core decomposition is a fundamental graph problem with a large number of applications. Most existing approaches for core decomposition assume that the graph is kept in memory of a machine. Nevertheless, many real-world graphs are big and may not reside in memory. In the literature, there is only one work for I/O efficient core decomposition that avoids loading the whole graph in memory. However, t... View full abstract»

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