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Knowledge and Data Engineering, IEEE Transactions on

Issue 10 • Date Oct. 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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  • On combining classifier mass functions for text categorization

    Publication Year: 2005 , Page(s): 1307 - 1319
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (768 KB) |  | HTML iconHTML  

    Experience shows that different text classification methods can give different results. We look here at a way of combining the results of two or more different classification methods using an evidential approach. The specific methods we have been experimenting with in our group include the support vector machine, kNN (nearest neighbors), kNN model-based approach (kNNM), and Rocchio methods, but th... View full abstract»

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  • Continuous similarity-based queries on streaming time series

    Publication Year: 2005 , Page(s): 1320 - 1332
    Cited by:  Papers (7)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1288 KB) |  | HTML iconHTML  

    In many applications, local or remote sensors send in streams of data, and the system needs to monitor the streams to discover relevant events/patterns and deliver instant reaction correspondingly. An important scenario is that the incoming stream is a continually appended time series, and the patterns are time series in a database. At each time when a new value arrives (called a time position), t... View full abstract»

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  • Using one-class and two-class SVMs for multiclass image annotation

    Publication Year: 2005 , Page(s): 1333 - 1346
    Cited by:  Papers (47)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1080 KB) |  | HTML iconHTML  

    We propose using one-class, two-class, and multiclass SVMs to annotate images for supporting keyword retrieval of images. Providing automatic annotation requires an accurate mapping of images' low-level perceptual features (e.g., color and texture) to some high-level semantic labels (e.g., landscape, architecture, and animals). Much work has been performed in this area; however, there is a lack of... View full abstract»

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  • Fast algorithms for frequent itemset mining using FP-trees

    Publication Year: 2005 , Page(s): 1347 - 1362
    Cited by:  Papers (93)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1704 KB) |  | HTML iconHTML  

    Efficient algorithms for mining frequent itemsets are crucial for mining association rules as well as for many other data mining tasks. Methods for mining frequent itemsets have been implemented using a prefix-tree structure, known as an FP-tree, for storing compressed information about frequent itemsets. Numerous experimental results have demonstrated that these algorithms perform extremely well.... View full abstract»

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  • An interactive approach to mining gene expression data

    Publication Year: 2005 , Page(s): 1363 - 1378
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1912 KB) |  | HTML iconHTML  

    Effective identification of coexpressed genes and coherent patterns in gene expression data is an important task in bioinformatics research and biomedical applications. Several clustering methods have recently been proposed to identify coexpressed genes that share similar coherent patterns. However, there is no objective standard for groups of coexpressed genes. The interpretation of co-expression... View full abstract»

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  • A data envelopment analysis-based approach for data preprocessing

    Publication Year: 2005 , Page(s): 1379 - 1388
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    In this paper, we show how the data envelopment analysis (DEA) model might be useful to screen training data so a subset of examples that satisfy monotonicity property can be identified. Using real-world health care and software engineering data, managerial monotonicity assumption, and artificial neural network (ANN) as a forecasting model, we illustrate that DEA-based data screening of training d... View full abstract»

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  • A shrinking-based clustering approach for multidimensional data

    Publication Year: 2005 , Page(s): 1389 - 1403
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1224 KB) |  | HTML iconHTML  

    Existing data analysis techniques have difficulty in handling multidimensional data. Multidimensional data has been a challenge for data analysis because of the inherent sparsity of the points. In this paper, we first present a novel data preprocessing technique called shrinking which optimizes the inherent characteristic of distribution of data. This data reorganization concept can be applied in ... View full abstract»

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  • State-space optimization of ETL workflows

    Publication Year: 2005 , Page(s): 1404 - 1419
    Cited by:  Papers (7)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1448 KB) |  | HTML iconHTML  

    Extraction-transformation-loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization, and insertion into a data warehouse. In this paper, we derive into the logical optimization of ETL processes, modeling it as a state-space search problem. We consider each ETL workflow as a state and fabricate the state space through a se... View full abstract»

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  • Pattern discovery on Australian medical claim data - a systematic approach

    Publication Year: 2005 , Page(s): 1420 - 1435
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2120 KB)  

    The national health insurance system in Australia records details on medical services and claims provided to its population. An effective method to the discovery of temporal behavioral patterns in the data set is proposed in this paper. The method consists of a two-step approach which is applied recursively to the data set. First, a clustering algorithm is used to segment the data into classes. Th... View full abstract»

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  • A formal framework for prefetching based on the type-level access pattern in object-relational DBMSs

    Publication Year: 2005 , Page(s): 1436 - 1448
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1016 KB) |  | HTML iconHTML  

    Prefetching is an effective method for minimizing the number of fetches between the client and the server in a database management system. In this paper, we formally define the notion of prefetching. We also formally propose new notions of the type-level access locality and type-level access pattern. The type-level access locality is a phenomenon that repetitive patterns exist in the attributes re... View full abstract»

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  • Call for Papers

    Publication Year: 2005 , Page(s): 1449
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  • [Advertisement]

    Publication Year: 2005 , Page(s): 1450
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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