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IEEE Transactions on Knowledge and Data Engineering

Issue 3 • Date March 2005

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

    Publication Year: 2005, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2005, Page(s): c2
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  • Using AUC and accuracy in evaluating learning algorithms

    Publication Year: 2005, Page(s):299 - 310
    Cited by:  Papers (246)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1344 KB) | HTML iconHTML

    The area under the ROC (receiver operating characteristics) curve, or simply AUC, has been traditionally used in medical diagnosis since the 1970s. It has recently been proposed as an alternative single-number measure for evaluating the predictive ability of learning algorithms. However, no formal arguments were given as to why AUC should be preferred over accuracy. We establish formal criteria fo... View full abstract»

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  • A tree-structured index allocation method with replication over multiple broadcast channels in wireless environments

    Publication Year: 2005, Page(s):311 - 325
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1944 KB) | HTML iconHTML

    Broadcast has often been used to disseminate frequently requested data efficiently to a large volume of mobile units over single or multiple channels. Since mobile units have limited battery power, the minimization of the access and tuning times for the broadcast data is an important problem. There have been many research efforts that focus on minimizing access and tuning times by providing indexe... View full abstract»

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  • Adaptive data access in broadcast-based wireless environments

    Publication Year: 2005, Page(s):326 - 338
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1176 KB) | HTML iconHTML

    Power conservation and client waiting time reduction are two important aspects of data access efficiency in broadcast-based wireless communication systems. The intention of data access methods is to optimize client power consumption with the least possible overhead on client waiting time. We propose an adaptive data access method which builds on the strengths of indexing and hashing techniques. We... View full abstract»

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  • Indexing high-dimensional data for efficient in-memory similarity search

    Publication Year: 2005, Page(s):339 - 353
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1432 KB) | HTML iconHTML

    In main memory systems, the L2 cache typically employs cache line sizes of 32-128 bytes. These values are relatively small compared to high-dimensional data, e.g., >32D. The consequence is that existing techniques (on low-dimensional data) that minimize cache misses are no longer effective. We present a novel index structure, called Δ-tree, to speed up the high-dimensional query in main memo... View full abstract»

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  • Divide-and-approximate: a novel constraint push strategy for iceberg cube mining

    Publication Year: 2005, Page(s):354 - 368
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1664 KB) | HTML iconHTML

    The iceberg cube mining computes all cells v, corresponding to GROUP BY partitions, that satisfy a given constraint on aggregated behaviors of the tuples in a GROUP BY partition. The number of cells often is so large that the result cannot be realistically searched without pushing the constraint into the search. Previous works have pushed antimonotone and monotone constraints. However, many useful... View full abstract»

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  • Projective clustering by histograms

    Publication Year: 2005, Page(s):369 - 383
    Cited by:  Papers (34)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1128 KB) | HTML iconHTML

    Recent research suggests that clustering for high-dimensional data should involve searching for "hidden" subspaces with lower dimensionalities, in which patterns can be observed when data objects are projected onto the subspaces. Discovering such interattribute correlations and location of the corresponding clusters is known as the projective clustering problem. We propose an efficient projective ... View full abstract»

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  • Semisupervised learning of hierarchical latent trait models for data visualization

    Publication Year: 2005, Page(s):384 - 400
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2608 KB) | HTML iconHTML

    Recently, we have developed the hierarchical generative topographic mapping (HGTM), an interactive method for visualization of large high-dimensional real-valued data sets. We propose a more general visualization system by extending HGTM in three ways, which allows the user to visualize a wider range of data sets and better support the model development process. 1) We integrate HGTM with noise mod... View full abstract»

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  • Relevant data expansion for learning concept drift from sparsely labeled data

    Publication Year: 2005, Page(s):401 - 412
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1400 KB) | HTML iconHTML

    Keeping track of changing interests is a natural phenomenon as well as an interesting tracking problem because interests can emerge and diminish at different time frames. Being able to do so with a few feedback examples poses an even more important and challenging problem because existing concept drift learning algorithms that handle the task typically suffer from it. This work presents a new comp... View full abstract»

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  • Analysis of data structures for admission control of advance reservation requests

    Publication Year: 2005, Page(s):413 - 424
    Cited by:  Papers (23)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (856 KB) | HTML iconHTML

    Advance reservations are a useful method to allocate resources of various kinds in many different environments. Among others, a major advantage of this kind of reservation is the improved admission probability for requests that are made sufficiently early. In order to implement reliable admission control for these requests, it is important to store information in data structures about future alloc... View full abstract»

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  • A flexible payment scheme and its role-based access control

    Publication Year: 2005, Page(s):425 - 436
    Cited by:  Papers (24)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1000 KB) | HTML iconHTML

    This work proposes a practical payment protocol with scalable anonymity for Internet purchases, and analyzes its role-based access control (RBAC). The protocol uses electronic cash for payment transactions. It is an offline payment scheme that can prevent a consumer from spending a coin more than once. Consumers can improve anonymity if they are worried about disclosure of their identities to bank... View full abstract»

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  • An extended Chi2 algorithm for discretization of real value attributes

    Publication Year: 2005, Page(s):437 - 441
    Cited by:  Papers (54)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (352 KB) | HTML iconHTML

    The variable precision rough sets (VPRS) model is a powerful tool for data mining, as it has been widely applied to acquire knowledge. Despite its diverse applications in many domains, the VPRS model unfortunately cannot be applied to real-world classification tasks involving continuous attributes. This requires a discretization method to preprocess the data. Discretization is an effective techniq... View full abstract»

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  • Additions to 2004 Annual Index

    Publication Year: 2005, Page(s): 442
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  • TKDE Information for authors

    Publication Year: 2005, Page(s): c3
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  • [Back cover]

    Publication Year: 2005, 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