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Knowledge and Data Engineering, IEEE Transactions on

Issue 1 • Date Jan. 2012

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Displaying Results 1 - 22 of 22
  • [Front cover]

    Publication Year: 2012 , Page(s): c1
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  • [Cover 2]

    Publication Year: 2012 , Page(s): c2
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  • A Framework for Learning Comprehensible Theories in XML Document Classification

    Publication Year: 2012 , Page(s): 1 - 14
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1266 KB) |  | HTML iconHTML  

    XML has become the universal data format for a wide variety of information systems. The large number of XML documents existing on the web and in other information storage systems makes classification an important task. As a typical type of semistructured data, XML documents have both structures and contents. Traditional text learning techniques are not very suitable for XML document classification... View full abstract»

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  • CoCITe—Coordinating Changes in Text

    Publication Year: 2012 , Page(s): 15 - 29
    Request Permissions | Click to expandAbstract | PDF file iconPDF (3036 KB) |  | HTML iconHTML  

    Text streams are ubiquitous and contain a wealth of information, but are typically orders of magnitude too large in scale for comprehensive human inspection. There is a need for tools that can detect and group changes occurring within text streams and substreams, in order to find, structure, and summarize these changes for presentation to human analysts. This paper describes a procedure for effici... View full abstract»

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  • Effective Pattern Discovery for Text Mining

    Publication Year: 2012 , Page(s): 30 - 44
    Cited by:  Papers (18)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1302 KB)  

    Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held ... View full abstract»

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  • Efficient Processing of Uncertain Events in Rule-Based Systems

    Publication Year: 2012 , Page(s): 45 - 58
    Cited by:  Papers (3)
    Multimedia
    Request Permissions | Click to expandAbstract | PDF file iconPDF (975 KB) |  | HTML iconHTML  

    There is a growing need for systems that react automatically to events. While some events are generated externally and deliver data across distributed systems, others need to be derived by the system itself based on available information. Event derivation is hampered by uncertainty attributed to causes such as unreliable data sources or the inability to determine with certainty whether an event ha... View full abstract»

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  • Fractal-Based Intrinsic Dimension Estimation and Its Application in Dimensionality Reduction

    Publication Year: 2012 , Page(s): 59 - 71
    Cited by:  Papers (5)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1342 KB) |  | HTML iconHTML  

    Dimensionality reduction is an important step in knowledge discovery in databases. Intrinsic dimension indicates the number of variables necessary to describe a data set. Two methods, box-counting dimension and correlation dimension, are commonly used for intrinsic dimension estimation. However, the robustness of these two methods has not been rigorously studied. This paper demonstrates that corre... View full abstract»

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  • Identifying Evolving Groups in Dynamic Multimode Networks

    Publication Year: 2012 , Page(s): 72 - 85
    Cited by:  Papers (6)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1448 KB) |  | HTML iconHTML  

    A multimode network consists of heterogeneous types of actors with various interactions occurring between them. Identifying communities in a multimode network can help understand the structural properties of the network, address the data shortage and unbalanced problems, and assist tasks like targeted marketing and finding influential actors within or between groups. In general, a network and its ... View full abstract»

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  • Incremental Information Extraction Using Relational Databases

    Publication Year: 2012 , Page(s): 86 - 99
    Cited by:  Papers (2)
    Multimedia
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1076 KB) |  | HTML iconHTML  

    Information extraction systems are traditionally implemented as a pipeline of special-purpose processing modules targeting the extraction of a particular kind of information. A major drawback of such an approach is that whenever a new extraction goal emerges or a module is improved, extraction has to be reapplied from scratch to the entire text corpus even though only a small part of the corpus mi... View full abstract»

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  • Labeling Dynamic XML Documents: An Order-Centric Approach

    Publication Year: 2012 , Page(s): 100 - 113
    Cited by:  Papers (1)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1367 KB) |  | HTML iconHTML  

    Dynamic XML labeling schemes have important applications in XML Database Management Systems. In this paper, we explore dynamic XML labeling schemes from a novel order-centric perspective. We compare the various labeling schemes proposed in the literature with a special focus on their orders of labels. We show that the order of labels fundamentally impacts the update performance of a labeling schem... View full abstract»

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  • Learning a Propagable Graph for Semisupervised Learning: Classification and Regression

    Publication Year: 2012 , Page(s): 114 - 126
    Cited by:  Papers (3)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1553 KB) |  | HTML iconHTML  

    In this paper, we present a novel framework, called learning by propagability, for two essential data mining tasks, i.e., classification and regression. The whole learning process is driven by the philosophy that the data labels and the optimal feature representation jointly constitute a harmonic system, where the data labels are invariant with respect to the propagation on the similarity graph co... View full abstract»

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  • Mutual Information-Based Supervised Attribute Clustering for Microarray Sample Classification

    Publication Year: 2012 , Page(s): 127 - 140
    Cited by:  Papers (7)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (2131 KB) |  | HTML iconHTML  

    Microarray technology is one of the important biotechnological means that allows to record the expression levels of thousands of genes simultaneously within a number of different samples. An important application of microarray gene expression data in functional genomics is to classify samples according to their gene expression profiles. Among the large amount of genes presented in gene expression ... View full abstract»

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  • SPIRE: Efficient Data Inference and Compression over RFID Streams

    Publication Year: 2012 , Page(s): 141 - 155
    Cited by:  Papers (5)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (1458 KB) |  | HTML iconHTML  

    Despite its promise, RFID technology presents numerous challenges, including incomplete data, lack of location and containment information, and very high volumes. In this work, we present a novel data inference and compression substrate over RFID streams to address these challenges. Our substrate employs a time-varying graph model to efficiently capture possible object locations and interobject re... View full abstract»

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  • Topic Mining over Asynchronous Text Sequences

    Publication Year: 2012 , Page(s): 156 - 169
    Cited by:  Papers (1)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (2319 KB) |  | HTML iconHTML  

    Time stamped texts, or text sequences, are ubiquitous in real-world applications. Multiple text sequences are often related to each other by sharing common topics. The correlation among these sequences provides more meaningful and comprehensive clues for topic mining than those from each individual sequence. However, it is nontrivial to explore the correlation with the existence of asynchronism am... View full abstract»

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  • TSCAN: A Content Anatomy Approach to Temporal Topic Summarization

    Publication Year: 2012 , Page(s): 170 - 183
    Cited by:  Papers (1)
    Request Permissions | Click to expandAbstract | PDF file iconPDF (2031 KB) |  | HTML iconHTML  

    A topic is defined as a seminal event or activity along with all directly related events and activities. It is represented by a chronological sequence of documents published by different authors on the Internet. In this study, we define a task called topic anatomy, which summarizes and associates the core parts of a topic temporally so that readers can understand the content easily. The proposed t... View full abstract»

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  • 2011 Reviewers List

    Publication Year: 2012 , Page(s): 184 - 189
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  • 2011 Annual Index

    Publication Year: 2012 , Page(s): Not in print
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  • New issue alerts [advertisement]

    Publication Year: 2012 , Page(s): 190
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  • What's new in Transactions [advertisement]

    Publication Year: 2012 , Page(s): 191
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  • New Transactions on Computers EssentialSet [advertisement]

    Publication Year: 2012 , Page(s): 192
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  • TKDE Information for authors

    Publication Year: 2012 , Page(s): c3
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  • [Cover 4]

    Publication Year: 2012 , 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