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Big Data (BigData Congress), 2013 IEEE International Congress on

Date June 27 2013-July 2 2013

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Displaying Results 1 - 25 of 80
  • [Front cover]

    Publication Year: 2013 , Page(s): C4
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  • [Title page i]

    Publication Year: 2013 , Page(s): i
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  • [Title page iii]

    Publication Year: 2013 , Page(s): iii
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  • [Copyright notice]

    Publication Year: 2013 , Page(s): iv
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  • Table of contents

    Publication Year: 2013 , Page(s): v - x
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  • Message from the General and Program Chairs

    Publication Year: 2013 , Page(s): xi
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  • Organizing Committee

    Publication Year: 2013 , Page(s): xii - xiv
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  • Program Committee

    Publication Year: 2013 , Page(s): xv - xvi
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  • Support team

    Publication Year: 2013 , Page(s): xvii
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  • IEEE Computer Society Technical Committee on Services Computing

    Publication Year: 2013 , Page(s): xviii
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  • A Database-Hadoop Hybrid Approach to Scalable Machine Learning

    Publication Year: 2013 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (406 KB) |  | HTML iconHTML  

    There are two popular schools of thought for performing large-scale machine learning that does not fit into memory. One is to run machine learning within a relational database management system, and the other is to push analytical functions into MapReduce. As each approach has its own set of pros and cons, we propose a database-Hadoop hybrid approach to scalable machine learning where batch-learni... View full abstract»

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  • Performance Overhead among Three Hypervisors: An Experimental Study Using Hadoop Benchmarks

    Publication Year: 2013 , Page(s): 9 - 16
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (173 KB) |  | HTML iconHTML  

    Hyper visors are widely used in cloud environments and their impact on application performance has been a topic of significant research and practical interest. We conducted experimental measurements of several benchmarks using Hadoop MapReduce to evaluate and compare the performance impact of three popular hyper visors: a commercial hyper visor, Xen, and KVM. We found that differences in the workl... View full abstract»

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  • Data Allocation in Scalable Distributed Database Systems Based on Time Series Forecasting

    Publication Year: 2013 , Page(s): 17 - 24
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (291 KB) |  | HTML iconHTML  

    In cloud computing environments, database systems have to serve a large number of tenants instantaneously and handle applications with different load characteristics. To provide a high quality of services, scalable distributed database systems with self-provisioning are required. The number of working nodes is adjusted dynamically based on user demand. Data fragments are reallocated frequently for... View full abstract»

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  • A Discussion of Privacy Challenges in User Profiling with Big Data Techniques: The EEXCESS Use Case

    Publication Year: 2013 , Page(s): 25 - 30
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (223 KB) |  | HTML iconHTML  

    User profiling is the process of collecting information about a user in order to construct their profile. The information in a user profile may include various attributes of a user such as geographical location, academic and professional background, membership in groups, interests, preferences, opinions, etc. Big data techniques enable collecting accurate and rich information for user profiles, in... View full abstract»

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  • Approximate Two-Party Privacy-Preserving String Matching with Linear Complexity

    Publication Year: 2013 , Page(s): 31 - 37
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (201 KB) |  | HTML iconHTML  

    Consider two parties who want to compare their strings, e.g., genomes, but do not want to reveal them to each other. We present a system for privacy-preserving matching of strings, which differs from existing systems by providing a deterministic approximation instead of an exact distance. It is efficient (linear complexity), non-interactive and does not involve a third party which makes it particu... View full abstract»

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  • Engineering Privacy for Big Data Apps with the Unified Modeling Language

    Publication Year: 2013 , Page(s): 38 - 45
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (916 KB) |  | HTML iconHTML  

    This paper describes proposed privacy extensions to UML to help software engineers to quickly visualize privacy requirements, and design privacy into big data applications. To adhere to legal requirements and/or best practices, big data applications will need to apply Privacy by Design principles and use privacy services, such as, and not limited to, anonymization, pseudonymization, security, noti... View full abstract»

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  • Milieu: Lightweight and Configurable Big Data Provenance for Science

    Publication Year: 2013 , Page(s): 46 - 53
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (328 KB) |  | HTML iconHTML  

    The volume and complexity of data produced and analyzed in scientific collaborations is growing exponentially. It is important to track scientific data-intensive analysis workflows to provide context and reproducibility as data is transformed in these collaborations. Provenance addresses this need and aids scientists by providing the lineage or history of how data is generated, used and modified. ... View full abstract»

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  • Consistent Process Mining over Big Data Triple Stores

    Publication Year: 2013 , Page(s): 54 - 61
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (634 KB) |  | HTML iconHTML  

    'Big Data' techniques are often adopted in cross-organization scenarios for integrating multiple data sources to extract statistics or other latent information. Even if these techniques do not require the support of a schema for processing data, a common conceptual model is typically defined to address name resolution. This implies that each local source is tasked of applying a semantic lifting pr... View full abstract»

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  • Towards Cloud-Based Analytics-as-a-Service (CLAaaS) for Big Data Analytics in the Cloud

    Publication Year: 2013 , Page(s): 62 - 69
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (766 KB) |  | HTML iconHTML  

    Data Analytics has proven its importance in knowledge discovery and decision support in different data and application domains. Big data analytics poses a serious challenge in terms of the necessary hardware and software resources. The cloud technology today offers a promising solution to this challenge by enabling ubiquitous and scalable provisioning of the computing resources. However, there are... View full abstract»

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  • Scalable and Trustworthy Cross-Enterprise WfMSs by Cloud Collaboration

    Publication Year: 2013 , Page(s): 70 - 77
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (284 KB) |  | HTML iconHTML  

    Establishing scalable and cross-enterprise workflow management systems (WfMSs) in the cloud requires the adaptation and extension of existing concepts for process management. This paper proposes a scalable and cross-enterprise WfMS with a multitenancy architecture. Especially, it can activate enactment of workflow processes by cloud collaboration. We do not employ the traditional engine-based WfMS... View full abstract»

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  • A Bandwidth-Conscious Caching Scheme for Mobile Devices

    Publication Year: 2013 , Page(s): 78 - 85
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (827 KB) |  | HTML iconHTML  

    While a substantial amount of big data are consumed via mobile devices, accessing content via wireless data connections on mobile devices has its own set of challenges. Among these challenges, speed of data transfer is usually our first priority. Although there are many fast data connections available for Web surfing (3G, LTE etc.), the actual connection speed could vary significantly among differ... View full abstract»

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  • Towards a Quality-centric Big Data Architecture for Federated Sensor Services

    Publication Year: 2013 , Page(s): 86 - 93
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (373 KB) |  | HTML iconHTML  

    As the Internet of Things (IoT) paradigm gains popularity, the next few years will likely witness 'servitization' of domain sensing functionalities. We envision a cloud-based eco-system in which high quality data from large numbers of independently-managed sensors is shared or even traded in real-time. Such an eco-system will necessarily have multiple stakeholders such as sensor data providers, do... View full abstract»

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  • Learning Classifiers from Chains of Multiple Interlinked RDF Data Stores

    Publication Year: 2013 , Page(s): 94 - 101
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (399 KB) |  | HTML iconHTML  

    The emergence of many interlinked, physically distributed, and autonomously maintained RDF stores offers unprecedented opportunities for predictive modeling and knowledge discovery from such data. However existing machine learning approaches are limited in their applicability because it is neither desirable nor feasible to gather all of the data in a centralized location for analysis due to access... View full abstract»

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  • Multi-resolution Social Network Community Identification and Maintenance on Big Data Platform

    Publication Year: 2013 , Page(s): 102 - 109
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (252 KB) |  | HTML iconHTML  

    Community identification in social networks is of great interest and with dynamic changes to its graph representation and content, the incremental maintenance of community poses significant challenges in computation. Moreover, the intensity of community engagement can be distinguished at multiple levels, resulting in a multi-resolution community representation that has to be maintained over time. ... View full abstract»

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  • Online Association Rule Mining over Fast Data

    Publication Year: 2013 , Page(s): 110 - 117
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1248 KB) |  | HTML iconHTML  

    To extract useful and actionable information in real-time, the information technology (IT) world is coping with big data problems today. In this paper, we present implementation details and performance results of ReCEPtor, our system for "online" Association Rule Mining (ARM) over big and fast data streams. Specifically, we added Apriori and two different FP-Growth algorithms inside Esper Complex ... View full abstract»

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