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IEEE Transactions on Knowledge and Data Engineering

Issue 9 • Sept. 2009

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Displaying Results 1 - 15 of 15
  • [Front cover]

    Publication Year: 2009, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2009, Page(s): c2
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  • Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval

    Publication Year: 2009, Page(s):1233 - 1248
    Cited by:  Papers (28)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4502 KB) | HTML iconHTML

    Most machine learning tasks in data classification and information retrieval require manually labeled data examples in the training stage. The goal of active learning is to select the most informative examples for manual labeling in these learning tasks. Most of the previous studies in active learning have focused on selecting a single unlabeled example in each iteration. This could be inefficient... View full abstract»

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  • Information-Theoretic Distance Measures for Clustering Validation: Generalization and Normalization

    Publication Year: 2009, Page(s):1249 - 1262
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2046 KB) | HTML iconHTML

    This paper studies the generalization and normalization issues of information-theoretic distance measures for clustering validation. Along this line, we first introduce a uniform representation of distance measures, defined as quasi-distance, which is induced based on a general form of conditional entropy. The quasi-distance possesses three properties: symmetry, the triangle law, and the minimum r... View full abstract»

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  • Learning from Imbalanced Data

    Publication Year: 2009, Page(s):1263 - 1284
    Cited by:  Papers (753)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1519 KB) | HTML iconHTML

    With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding of knowledge discovery and analysis from raw data to support decision-making processes. Although existing knowledge discovery and data engineering techniques have shown great succe... View full abstract»

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  • Nonlinear Dimensionality Reduction with Local Spline Embedding

    Publication Year: 2009, Page(s):1285 - 1298
    Cited by:  Papers (46)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2697 KB) | HTML iconHTML

    This paper presents a new algorithm for nonlinear dimensionality reduction (NLDR). Our algorithm is developed under the conceptual framework of compatible mapping. Each such mapping is a compound of a tangent space projection and a group of splines. Tangent space projection is estimated at each data point on the manifold, through which the data point itself and its neighbors are represented in tan... View full abstract»

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  • Patch Alignment for Dimensionality Reduction

    Publication Year: 2009, Page(s):1299 - 1313
    Cited by:  Papers (206)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3669 KB) | HTML iconHTML

    Spectral analysis-based dimensionality reduction algorithms are important and have been popularly applied in data mining and computer vision applications. To date many algorithms have been developed, e.g., principal component analysis, locally linear embedding, Laplacian eigenmaps, and local tangent space alignment. All of these algorithms have been designed intuitively and pragmatically, i.e., on... View full abstract»

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  • Visible Reverse k-Nearest Neighbor Query Processing in Spatial Databases

    Publication Year: 2009, Page(s):1314 - 1327
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2811 KB) | HTML iconHTML

    Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g., buildings) and their presence may affect the visibility between objects. In this paper, we introduce a novel vari... View full abstract»

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  • Result Merging Technique for Answering XPath Query over XSLT Transformed Data

    Publication Year: 2009, Page(s):1328 - 1342
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5773 KB) | HTML iconHTML

    Caching stores the results of previously answered queries in order to answer succeeding queries faster by reusing these results. We propose two different approaches for using caches of XSLT transformed XML data in order to answer queries. The first approach checks whether or not a current query Q can be directly answered from the result of a previously answered query Qi stored in the cache. The ne... View full abstract»

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  • Optimization Techniques for Reactive Network Monitoring

    Publication Year: 2009, Page(s):1343 - 1357
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1674 KB) | HTML iconHTML

    We develop a framework for minimizing the communication overhead of monitoring global system parameters in IP networks and sensor networks. A global system predicate is defined as a conjunction of the local properties of different network elements. A typical example is to identify the time windows when the outbound traffic from each network element exceeds a predefined threshold. Our main idea is ... View full abstract»

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  • Call for Papers: Cloud Data Management

    Publication Year: 2009, Page(s): 1358
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  • IEEE Computer Society CSDP Certification [advertisement]

    Publication Year: 2009, Page(s): 1359
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  • IEEE Computer Society Computing Now [advertisement]

    Publication Year: 2009, Page(s): 1360
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  • TKDE Information for authors

    Publication Year: 2009, Page(s): c3
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  • [Back cover]

    Publication Year: 2009, 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.

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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