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2017 IEEE 33rd International Conference on Data Engineering (ICDE)

19-22 April 2017

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Displaying Results 1 - 25 of 243
  • [Front cover]

    Publication Year: 2017, Page(s): c1
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  • [Title page i]

    Publication Year: 2017, Page(s): i
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  • [Title page iii]

    Publication Year: 2017, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2017, Page(s): iv
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  • Table of contents

    Publication Year: 2017, Page(s):v - xxiv
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  • Message from the Chairs

    Publication Year: 2017, Page(s):xxv - xxvi
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  • Organizing Committee

    Publication Year: 2017, Page(s):xxvii - xxviii
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  • Reviewers

    Publication Year: 2017, Page(s):xxix - xxxiv
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  • Mosaics: Stratosphere, Flink and Beyond

    Publication Year: 2017, Page(s): 3
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (834 KB)

    The global database research community has greatly impacted the functionality and performance of data storage and processing systems along the dimensions that define “big data”, i.e., volume, velocity, variety, and veracity. Locally, over the past five years, we have also been working on varying fronts. Among our contributions are: (1) establishing a vision for a database-inspired bi... View full abstract»

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  • Leveraging Data and People to Accelerate Data Science

    Publication Year: 2017, Page(s): 4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (830 KB)

    Doing data science - extracting insight by analyzing data - is not easy. Data science is used to answer interesting questions that typically involve multiple diverse data sources, many different types of analysis, and often, large and messy data volumes. To answer one of these questions, several types of expertise may be needed to understand the context and domain being served, to import and trans... View full abstract»

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  • Semantic Bootstrapping: A Theoretical Perspective

    Publication Year: 2017, Page(s):7 - 8
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (849 KB) | HTML iconHTML

    Knowledge acquisition is an iterative process. Most prior work used syntactic bootstrapping approaches, while semantic bootstrapping was proposed recently. Unlike syntactic bootstrapping, semantic bootstrapping bootstraps directly on knowledge rather than on syntactic patterns, that is, it uses existing knowledge to understand the text and acquire more knowledge. It has been shown that semantic bo... View full abstract»

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  • IF-Matching: Towards Accurate Map-Matching with Information Fusion

    Publication Year: 2017, Page(s):9 - 10
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (826 KB) | HTML iconHTML

    With the advance of various location-acquisition technologies, a myriad of GPS trajectories can be collected every day. However, the raw coordinate data captured by sensors often cannot reflect real positions due to many physical constraints and some rules of law. How to accurately match GPS trajectories to roads on a digital map is an important issue. Many existing methods still cannot meet strin... View full abstract»

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  • A Mixed Generative-Discriminative Based Hashing Method

    Publication Year: 2017, Page(s):11 - 12
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (909 KB) | HTML iconHTML

    Hashing methods have proven to be useful for a variety of tasks and have attracted extensive attention in recent years. Various hashing approaches have been proposed to capture similarities between textual, visual, and cross-media information. However, most of the existing works use a bag-of-words methods to represent textual information. Since words with different forms may have similar meaning, ... View full abstract»

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  • SPIRIT: A Tree Kernel-Based Method for Topic Person Interaction Detection (Extended Abstract)

    Publication Year: 2017, Page(s):13 - 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (908 KB) | HTML iconHTML

    In this paper, we investigate the interactions between topic persons to help readers construct the background knowledge of a topic. We proposed a rich interactive tree structure to represent syntactic, context, and semantic information of text, and this structure is incorporated into a tree-based convolution kernel to identify segments that convey person interactions and further construct person i... View full abstract»

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  • Efficient Cache-Supported Path Planning on Roads (Extended Abstract)

    Publication Year: 2017, Page(s):15 - 16
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (881 KB) | HTML iconHTML

    Owing to the wide availability of the global positioning system (GPS) and digital mapping of roads, road network navigation services have become a basic application on many mobile devices. Path planning, a fundamental function of road network navigation services, finds a route between the specified start location and destination. The efficiency of this path planning function is critical for mobile... View full abstract»

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  • Personalized Influential Topic Search via Social Network Summarization

    Publication Year: 2017, Page(s):17 - 18
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (973 KB) | HTML iconHTML

    Social networks have become a vital mechanism to disseminate information to friends and colleagues. But the dynamic nature of information and user connectivity within these networks raised many new and challenging research problems. One of them is the query-related topic search in social networks. In this work, we investigate the important problem of the personalized influential topic search. Ther... View full abstract»

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  • Recommendation for repeat consumption from user implicit feedback (extended abstract)

    Publication Year: 2017, Page(s):19 - 20
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (924 KB) | HTML iconHTML

    Most of the previous work on recommender systems focuses on discovering novel items that meet users' personalized interest. But there is barely any study about recommending repeat items that consumed by the target user before. In fact, people's consumption behaviors are a mixture of repeat and novelty-seeking behaviors [1]. Since people forget about things as time elapses, it is possible that user... View full abstract»

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  • PINOCCHIO: Probabilistic Influence-Based Location Selection over Moving Objects

    Publication Year: 2017, Page(s):21 - 22
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (853 KB)

    The location selection (LS) problem aims to mine the optimal location to place a new facility from a set of candidates such that the benefit or influence on a given set of objects is maximized. State-of-the-art LS techniques assume each object is static and can only be influenced by a single facility. However, in reality, objects (e.g., people, vehicles) are mobile and are influenced by multiple f... View full abstract»

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  • K-Join: Knowledge-Aware Similarity Join

    Publication Year: 2017, Page(s):23 - 24
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (840 KB) | HTML iconHTML

    Similarity join is a fundamental operation in data cleaning and integration. Existing similarity-join methods utilize the string similarity to quantify the relevance but neglect the knowledge behind the data, which plays an important role in understanding the data. Thanks to public knowledge bases, e.g., Freebase and Yago, we have an opportunity to use the knowledge to improve similarity join. To ... View full abstract»

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  • Mining suspicious tax evasion groups in big data (extended abstract)

    Publication Year: 2017, Page(s):25 - 26
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (919 KB) | HTML iconHTML

    There is evidence that an increasing number of enterprises plot together to evade tax in an unperceived way. At the same time, the taxation information related data is a classic kind of big data. These issues challenge the effectiveness of traditional data mining-based tax evasion detection methods. To address this problem, we first investigate the classic tax evasion cases, and employ a graph-bas... View full abstract»

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  • Influence Maximization in Trajectory Databases

    Publication Year: 2017, Page(s):27 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (967 KB) | HTML iconHTML

    We study a novel problem of influence maximization in trajectory databases that is very useful in precise locationaware advertising. It finds k best trajectories to be attached with a given advertisement and maximizes the expected influence among a large group of audience. We show that the problem is NP-hard and propose both exact and approximate solutions to find the best set of trajectories. We ... View full abstract»

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  • A Generic Method for Accelerating LSH-Based Similarity Join Processing (Extended Abstract)

    Publication Year: 2017, Page(s):29 - 30
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (846 KB) | HTML iconHTML

    Locality sensitive hashing (LSH) is an efficient method for solving the problem of approximate similarity search in high-dimensional spaces. Through LSH, a high-dimensional similarity join can be processed in the same way as hash join, making the cost of joining two large datasets linear. By judicially analyzing the properties of multiple LSH algorithms, we propose a generic method to accelerate t... View full abstract»

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  • The Moving K Diversified Nearest Neighbor Query

    Publication Year: 2017, Page(s):31 - 32
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1237 KB) | HTML iconHTML

    We study result diversification in continuous spatial query processing and formulate a new type of queries, the moving k diversified nearest neighbor query (MkDNN). Given a moving query object, an MkDNN query maintains continuously the k diversified nearest neighbors of the query object. Here, how diversified the nearest neighbors are is defined on the distance between the nearest neighbors. We pr... View full abstract»

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  • The interaction between schema matching and record matching in data integration (extended abstract)

    Publication Year: 2017, Page(s):33 - 34
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1101 KB) | HTML iconHTML

    Schema Matching (SM) and Record Matching (RM) are two necessary steps in integrating multiple relational tables of different schemas, where SM unifies the schemas and RM detects records referring to the same real-world entity. The two processes have been thoroughly studied separately, but few attention has been paid to the interaction of SM and RM. In this work we find that, even alternating them ... View full abstract»

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  • Learning mixtures of markov chains from aggregate data with structural constraints (extended abstract)

    Publication Year: 2017, Page(s):35 - 36
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1581 KB) | HTML iconHTML

    In this work, we explore the learning task of mixtures of Markov chains (MMCs) from aggregate data. Our work demonstrates that although this challenging task is generally intractable because of the identifiability problem, it can be solved approximately by imposing structural constraints on its transition matrices Specifically, the proposed structural constraints include specifying active state se... View full abstract»

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