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Knowledge and Data Engineering, IEEE Transactions on

Issue 2 • Date Feb. 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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  • Combining partitional and hierarchical algorithms for robust and efficient data clustering with cohesion self-merging

    Publication Year: 2005 , Page(s): 145 - 159
    Cited by:  Papers (18)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (2800 KB) |  | HTML iconHTML  

    Data clustering has attracted a lot of research attention in the field of computational statistics and data mining. In most related studies, the dissimilarity between two clusters is defined as the distance between their centroids or the distance between two closest (or farthest) data points However, all of these measures are vulnerable to outliers and removing the outliers precisely is yet anothe... View full abstract»

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  • Fast detection of XML structural similarity

    Publication Year: 2005 , Page(s): 160 - 175
    Cited by:  Papers (34)  |  Patents (4)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1728 KB) |  | HTML iconHTML  

    Because of the widespread diffusion of semistructured data in XML format, much research effort is currently devoted to support the storage and retrieval of large collections of such documents. XML documents can be compared as to their structural similarity, in order to group them into clusters so that different storage, retrieval, and processing techniques can be effectively exploited. In this sce... View full abstract»

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  • Iterative projected clustering by subspace mining

    Publication Year: 2005 , Page(s): 176 - 189
    Cited by:  Papers (17)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1488 KB) |  | HTML iconHTML  

    Irrelevant attributes add noise to high-dimensional clusters and render traditional clustering techniques inappropriate. Recently, several algorithms that discover projected clusters and their associated subspaces have been proposed. We realize the analogy between mining frequent itemsets and discovering dense projected clusters around random points. Based on this, we propose a technique that impr... View full abstract»

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  • Mining closed and maximal frequent subtrees from databases of labeled rooted trees

    Publication Year: 2005 , Page(s): 190 - 202
    Cited by:  Papers (25)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1224 KB) |  | HTML iconHTML  

    Tree structures are used extensively in domains such as computational biology, pattern recognition, XML databases, computer networks, and so on. One important problem in mining databases of trees is to find frequently occurring subtrees. Because of the combinatorial explosion, the number of frequent subtrees usually grows exponentially with the size of frequent subtrees and, therefore, mining all ... View full abstract»

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  • Outlier mining in large high-dimensional data sets

    Publication Year: 2005 , Page(s): 203 - 215
    Cited by:  Papers (73)  |  Patents (1)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1208 KB) |  | HTML iconHTML  

    A new definition of distance-based outlier and an algorithm, called HilOut, designed to efficiently detect the top n outliers of a large and high-dimensional data set are proposed. Given an integer k, the weight of a point is defined as the sum of the distances separating it from its k nearest-neighbors. Outlier are those points scoring the largest values of weight. The algorithm HilOut makes use ... View full abstract»

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  • Genetic evolution processing of data structures for image classification

    Publication Year: 2005 , Page(s): 216 - 231
    Cited by:  Papers (10)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1672 KB) |  | HTML iconHTML  

    This paper describes a method of structural pattern recognition based on a genetic evolution processing of data structures with neural networks representation. Conventionally, one of the most popular learning formulations of data structure processing is backpropagation through structures (BPTS) [C. Goller et al., (1996)]. The BPTS algorithm has been successfully applied to a number of learning tas... View full abstract»

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  • Preserving privacy by de-identifying face images

    Publication Year: 2005 , Page(s): 232 - 243
    Cited by:  Papers (69)  |  Patents (6)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1080 KB) |  | HTML iconHTML  

    In the context of sharing video surveillance data, a significant threat to privacy is face recognition software, which can automatically identify known people, such as from a database of drivers' license photos, and thereby track people regardless of suspicion. This paper introduces an algorithm to protect the privacy of individuals in video surveillance data by deidentifying faces such that many ... View full abstract»

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  • Evaluation and design of online cooperative feedback mechanisms for reputation management

    Publication Year: 2005 , Page(s): 244 - 254
    Cited by:  Papers (33)  |  Patents (2)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (712 KB) |  | HTML iconHTML  

    This research evaluates and analyzes existing mechanisms of online reputation systems based on cooperative feedbacks of past transaction information. We find existing popular feedback systems do not provide sustained incentives for sellers to behave honestly over time. We propose a new design of reputation system based on exponential smoothing. This mechanism is shown to be more robust compared to... View full abstract»

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  • Rewriting rules to permeate complex similarity and fuzzy queries within a relational database system

    Publication Year: 2005 , Page(s): 255 - 270
    Cited by:  Papers (5)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1624 KB) |  | HTML iconHTML  

    In recent years, the availability of complex data repositories (e.g., multimedia, genomic, semistructured databases) has paved the way to new potentials as to data querying. In this scenario, similarity and fuzzy techniques have proven to be successful principles for effective data retrieval. However, most proposals are domain specific and lack of a general and integrated approach to deal with gen... View full abstract»

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  • Spatiotemporal aggregate computation: a survey

    Publication Year: 2005 , Page(s): 271 - 286
    Cited by:  Papers (15)  |  Patents (3)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (656 KB) |  | HTML iconHTML  

    Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and s... View full abstract»

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  • [Advertisement]

    Publication Year: 2005 , Page(s): 287
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  • [Advertisement]

    Publication Year: 2005 , Page(s): 288
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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.

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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