IEEE Transactions on Knowledge and Data Engineering

Issue 6 • Nov.-Dec. 1999

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Displaying Results 1 - 14 of 14
  • Author index

    Publication Year: 1999, Page(s):999 - 1001
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    Freely Available from IEEE
  • Subject index

    Publication Year: 1999, Page(s):1001 - 1008
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  • Data consistency in intermittently connected distributed systems

    Publication Year: 1999, Page(s):896 - 915
    Cited by:  Papers (38)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1268 KB)

    Mobile computing introduces a new form of distributed computation in which communication is most often intermittent, low-bandwidth, or expensive, thus providing only weak connectivity. We present a replication scheme tailored for such environments. Bounded inconsistency is defined by allowing controlled deviation among copies located at weakly connected sites. A dual database interface is proposed... View full abstract»

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  • A one-phase algorithm to detect distributed deadlocks in replicated databases

    Publication Year: 1999, Page(s):880 - 895
    Cited by:  Papers (17)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (988 KB)

    Replicated databases that use quorum-consensus algorithms to perform majority voting are prone to deadlocks. Due to the P-out-of-Q nature of quorum requests, deadlocks that arise are generalized deadlocks and are hard to detect. We present an efficient distributed algorithm to detect generalized deadlocks in replicated databases. The algorithm performs reduction of a distributed wait-for-graph (WF... View full abstract»

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  • Knowledge discovery by inductive neural networks

    Publication Year: 1999, Page(s):992 - 998
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (468 KB)

    A new neural network model for inducing symbolic knowledge from empirical data is presented. This model capitalizes on the fact that the certainty factor-based activation function can improve the network generalization performance from a limited amount of training data. The formal properties of the procedure for extracting symbolic knowledge from such a trained neural network are investigated. In ... View full abstract»

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  • Automatic text categorization and its application to text retrieval

    Publication Year: 1999, Page(s):865 - 879
    Cited by:  Papers (47)  |  Patents (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (848 KB)

    We develop an automatic text categorization approach and investigate its application to text retrieval. The categorization approach is derived from a combination of a learning paradigm known as instance-based learning and an advanced document retrieval technique known as retrieval feedback. We demonstrate the effectiveness of our categorization approach using two real-world document collections fr... View full abstract»

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  • Generalized Analytic Rule Extraction for feedforward neural networks

    Publication Year: 1999, Page(s):985 - 991
    Cited by:  Papers (24)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB)

    We suggest the Input-Network-Training-Output-Extraction-Knowledge framework to classify existing rule extraction algorithms for feedforward neural networks. Based on the suggested framework, we identify the major practices of existing algorithms as relying on the technique of generate and test, which leads to exponential complexity, relying on specialized network structure and training algorithms,... View full abstract»

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  • Pattern discovery by residual analysis and recursive partitioning

    Publication Year: 1999, Page(s):833 - 852
    Cited by:  Papers (24)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1104 KB)

    In this paper, a novel method of pattern discovery is proposed. It is based on the theoretical formulation of a contingency table of events. Using residual analysis and recursive partitioning, statistically significant events are identified in a data set. These events constitute the important information contained in the data set and are easily interpretable as simple rules, contour plots, or para... View full abstract»

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  • The impact of data quality information on decision making: an exploratory analysis

    Publication Year: 1999, Page(s):853 - 864
    Cited by:  Papers (43)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (712 KB)

    This paper describes an experiment that explores the consequences of providing information regarding the quality of data used in decision making. The subjects in the study were given three types of information about the data's quality: none, two-point ordinal, and interval scale. This information was made available to the subjects, along with the actual data. Two decision strategies were explored:... View full abstract»

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  • Finding interesting patterns using user expectations

    Publication Year: 1999, Page(s):817 - 832
    Cited by:  Papers (50)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (936 KB)

    One of the major problems in the field of knowledge discovery (or data mining) is the interestingness problem. Past research and applications have found that, in practice, it is all too easy to discover a huge number of patterns in a database. Most of these patterns are actually useless or uninteresting to the user. But due to the huge number of patterns, it is difficult for the user to comprehend... View full abstract»

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  • Qualitative and quantitative temporal constraints and relational databases: theory, architecture, and applications

    Publication Year: 1999, Page(s):948 - 968
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1448 KB)

    Many different applications in different areas need to deal with both: databases, in order to take into account large amounts of structured data; and quantitative and qualitative temporal constraints about such data. We propose an approach that extends: temporal databases and artificial intelligence temporal reasoning techniques and integrate them in order to face such a need. Regarding temporal r... View full abstract»

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  • Multilevel filtering for high-dimensional image data: why and how

    Publication Year: 1999, Page(s):916 - 928
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (828 KB)

    It has been shown that filtering is a promising way to support efficient content-based retrieval from image data. However, all existing studies on filtering restrict their attention to two levels. We consider filtering structures that have at least three levels. In the first half of the paper, by analyzing the CPU and I/O costs of various structures, we provide analytic evidence on why three-level... View full abstract»

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  • Indexing valid time databases via B+-trees

    Publication Year: 1999, Page(s):929 - 947
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1188 KB)

    We present an approach, named MAP21, which uses standard B+ -trees to provide efficient indexing of valid time ranges. The MAP21 approach is based on mapping one dimensional ranges to one dimensional points where the lexicographical order among the ranges is preserved. The proposed approach may employ more than one tree, each indexing a disjoint subset of the indexed data. When compared... View full abstract»

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  • Linear spiral hashing for expansible files

    Publication Year: 1999, Page(s):969 - 984
    Cited by:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (856 KB)

    The goal of dynamic hashing is to design a function and a file structure that allow the address space allocated to the file to be increased and reduced without reorganizing the whole file. We propose a new scheme for dynamic hashing in which the growth of a file occurs at a rate of n+k/n per full expansion, where n is the number of pages of the file and k is a given integer constant which is small... View full abstract»

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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
Xuemin Lin
University of New South Wales

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