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IEEE Transactions on Knowledge and Data Engineering

Issue 5 • Date May 2011

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Displaying Results 1 - 16 of 16
  • [Front cover]

    Publication Year: 2011, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2011, Page(s): c2
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  • Authenticated Multistep Nearest Neighbor Search

    Publication Year: 2011, Page(s):641 - 654
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2088 KB) | HTML iconHTML

    Multistep processing is commonly used for nearest neighbor (NN) and similarity search in applications involving high-dimensional data and/or costly distance computations. Today, many such applications require a proof of result correctness. In this setting, clients issue NN queries to a server that maintains a database signed by a trusted authority. The server returns the NN set along with suppleme... View full abstract»

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  • Branch-and-Bound for Model Selection and Its Computational Complexity

    Publication Year: 2011, Page(s):655 - 668
    Cited by:  Papers (12)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2655 KB) | HTML iconHTML

    Branch-and-bound methods are used in various data analysis problems, such as clustering, seriation and feature selection. Classical approaches of branch-and-bound based clustering search through combinations of various partitioning possibilities to optimize a clustering cost. However, these approaches are not practically useful for clustering of image data where the size of data is large. Addition... View full abstract»

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  • Cosdes: A Collaborative Spam Detection System with a Novel E-Mail Abstraction Scheme

    Publication Year: 2011, Page(s):669 - 682
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1460 KB) | HTML iconHTML

    E-mail communication is indispensable nowadays, but the e-mail spam problem continues growing drastically. In recent years, the notion of collaborative spam filtering with near-duplicate similarity matching scheme has been widely discussed. The primary idea of the similarity matching scheme for spam detection is to maintain a known spam database, formed by user feedback, to block subsequent near-d... View full abstract»

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  • Discovering Conditional Functional Dependencies

    Publication Year: 2011, Page(s):683 - 698
    Cited by:  Papers (23)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1238 KB) | HTML iconHTML

    This paper investigates the discovery of conditional functional dependencies (CFDs). CFDs are a recent extension of functional dependencies (FDs) by supporting patterns of semantically related constants, and can be used as rules for cleaning relational data. However, finding quality CFDs is an expensive process that involves intensive manual effort. To effectively identify data cleaning rules, we ... View full abstract»

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  • Intertemporal Discount Factors as a Measure of Trustworthiness in Electronic Commerce

    Publication Year: 2011, Page(s):699 - 712
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (505 KB) | HTML iconHTML Multimedia Media

    In multiagent interactions, such as e-commerce and file sharing, being able to accurately assess the trustworthiness of others is important for agents to protect themselves from losing utility. Focusing on rational agents in e-commerce, we prove that an agent's discount factor (time preference of utility) is a direct measure of the agent's trustworthiness for a set of reasonably general assumption... View full abstract»

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  • Mining Discriminative Patterns for Classifying Trajectories on Road Networks

    Publication Year: 2011, Page(s):713 - 726
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (973 KB) | HTML iconHTML

    Classification has been used for modeling many kinds of data sets, including sets of items, text documents, graphs, and networks. However, there is a lack of study on a new kind of data, trajectories on road networks. Modeling such data is useful with the emerging GPS and RFID technologies and is important for effective transportation and traffic planning. In this work, we study methods for classi... View full abstract»

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  • Pareto-Based Dominant Graph: An Efficient Indexing Structure to Answer Top-K Queries

    Publication Year: 2011, Page(s):727 - 741
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2568 KB) | HTML iconHTML

    Given a record set D and a query score function F, a top-k query returns k records from D, whose values of function F on their attributes are the highest. In this paper, we investigate the intrinsic connection between top-k queries and dominant relationships between records, and based on which, we propose an efficient layer-based indexing structure, Pareto-Based Dominant Graph (DG), to improve the... View full abstract»

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  • RFID Data Processing in Supply Chain Management Using a Path Encoding Scheme

    Publication Year: 2011, Page(s):742 - 758
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5631 KB) | HTML iconHTML

    RFID technology can be applied to a broad range of areas. In particular, RFID is very useful in the area of business, such as supply chain management. However, the amount of RFID data in such an environment is huge. Therefore, much time is needed to extract valuable information from RFID data for supply chain management. In this paper, we present an efficient method to process a massive amount of ... View full abstract»

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  • Semantic Knowledge-Based Framework to Improve the Situation Awareness of Autonomous Underwater Vehicles

    Publication Year: 2011, Page(s):759 - 773
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1176 KB) | HTML iconHTML

    This paper proposes a semantic world model framework for hierarchical distributed representation of knowledge in autonomous underwater systems. This framework aims to provide a more capable and holistic system, involving semantic interoperability among all involved information sources. This will enhance interoperability, independence of operation, and situation awareness of the embedded service-or... View full abstract»

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  • SwiftRule: Mining Comprehensible Classification Rules for Time Series Analysis

    Publication Year: 2011, Page(s):774 - 787
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2362 KB) | HTML iconHTML

    In this article, we provide a new technique for temporal data mining which is based on classification rules that can easily be understood by human domain experts. Basically, time series are decomposed into short segments, and short-term trends of the time series within the segments (e.g., average, slope, and curvature) are described by means of polynomial models. Then, the classifiers assess short... View full abstract»

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  • When Does Cotraining Work in Real Data?

    Publication Year: 2011, Page(s):788 - 799
    Cited by:  Papers (21)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1029 KB) | HTML iconHTML

    Cotraining, a paradigm of semisupervised learning, is promised to alleviate effectively the shortage of labeled examples in supervised learning. The standard two-view cotraining requires the data set to be described by two views of features, and previous studies have shown that cotraining works well if the two views satisfy the sufficiency and independence assumptions. In practice, however, these ... View full abstract»

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  • IEEE and IEEE Computer Society Special Student Offer

    Publication Year: 2011, Page(s): 800
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    Freely Available from IEEE
  • TKDE Information for authors

    Publication Year: 2011, Page(s): c3
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  • [Back cover]

    Publication Year: 2011, Page(s): c4
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Aims & Scope

IEEE Transactions on Knowledge and Data Engineering (TKDE) informs researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Jian Pei
Simon Fraser University

Associate Editor-in-Chief
Xuemin Lin
University of New South Wales

Associate Editor-in-Chief
Lei Chen
Hong Kong University of Science and Technology