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Fifth IEEE International Conference on Data Mining (ICDM'05)

27-30 Nov. 2005

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Displaying Results 1 - 25 of 155
  • Fifth IEEE International Conference on Data Mining - Cover

    Publication Year: 2005, Page(s): c1
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  • Proceedings. Fifth IEEE International Conference on Data Mining

    Publication Year: 2005
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  • Fifth IEEE International Conference on Data Mining - Copyright Page

    Publication Year: 2005, Page(s): iv
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  • Fifth IEEE International Conference on Data Mining - Table of contents

    Publication Year: 2005, Page(s):v - xiv
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  • Welcome Message from the Conference Chairs

    Publication Year: 2005, Page(s): xv
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  • Welcome to ICDM 2005

    Publication Year: 2005, Page(s):xvi - xvii
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  • Conference organization

    Publication Year: 2005, Page(s):xviii - xix
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  • Steering Committee

    Publication Year: 2005, Page(s): xx
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  • Program Committee

    Publication Year: 2005, Page(s):xxi - xxiv
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  • Non-PC Reviewers

    Publication Year: 2005, Page(s):xxv - xxvi
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  • Top 10 data mining mistakes

    Publication Year: 2005
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (46 KB)

    Summary form only given. Data mining is still as much it is an art as a science, and fancy new tools make it easy to do wrong things with one's data even faster. We'll examine the major "cracks in the crystal ball" through case studies, both simple and complex, of (often personal) errors - drawn from real-world consulting engagements. Best practices for data mining will be (accidentally) illuminat... View full abstract»

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  • Tutorials

    Publication Year: 2005, Page(s): 839
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (38 KB) | HTML iconHTML

    Provides an abstract for each of the tutorial presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Workshops

    Publication Year: 2005, Page(s): 840
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  • Panel Session

    Publication Year: 2005, Page(s): 841
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  • Handling generalized cost functions in the partitioning optimization problem through sequential binary programming

    Publication Year: 2005
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (176 KB) | HTML iconHTML

    This paper proposes a framework for cost-sensitive classification under a generalized cost function. By combining decision trees with sequential binary programming, we can handle unequal misclassification costs, constrained classification, and complex objective functions that other methods cannot. Our approach has two main contributions. First, it provides a new method for cost-sensitive classific... View full abstract»

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  • Online hierarchical clustering in a data warehouse environment

    Publication Year: 2005
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (248 KB) | HTML iconHTML

    Many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. Since a data warehouse is typically updated periodically in a batch mode, the mined patterns have to be updated as well. This requires not only accuracy from data mining methods but also fast availability of up-to-date knowledge, particularly in the presence of a ... View full abstract»

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  • eMailSift: eMail classification based on structure and content

    Publication Year: 2005
    Cited by:  Papers (1)  |  Patents (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (160 KB) | HTML iconHTML

    In this paper we propose a novel approach that uses structure as well as the content of emails in a folder for email classification. Our approach is based on the premise that representative - common and recurring -structures/patterns can be extracted from a pre-classified email folder and the same can be used effectively for classifying incoming emails. A number of factors that influence represent... View full abstract»

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  • An empirical Bayes approach to detect anomalies in dynamic multidimensional arrays

    Publication Year: 2005
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (208 KB) | HTML iconHTML

    We consider the problem of detecting anomalies in data that arise as multidimensional arrays with each dimension corresponding to the levels of a categorical variable. In typical data mining applications, the number of cells in such arrays is usually large. Our primary focus is detecting anomalies by comparing information at the current time to historical data. Naive approaches advocated in the pr... View full abstract»

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  • Classifier fusion using shared sampling distribution for boosting

    Publication Year: 2005
    Cited by:  Papers (3)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (352 KB) | HTML iconHTML

    We present a new framework for classifier fusion that uses a shared sampling distribution for obtaining a weighted classifier ensemble. The weight update process is self regularizing as subsequent classifiers trained on the disjoint views rectify the bias introduced by any classifier in preceding iterations. We provide theoretical guarantees that our approach indeed provides results which are bett... View full abstract»

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  • Improving automatic query classification via semi-supervised learning

    Publication Year: 2005
    Cited by:  Papers (17)  |  Patents (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (176 KB) | HTML iconHTML

    Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose Web search systems. Such classification becomes critical if the system is to return results not just from a general Web collection but from topic-specific back-end databases as well. Maintaining sufficient classification recall is very difficult as Web queries are typically short, y... View full abstract»

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  • ViVo: visual vocabulary construction for mining biomedical images

    Publication Year: 2005
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2680 KB) | HTML iconHTML

    Given a large collection of medical images of several conditions and treatments, how can we succinctly describe the characteristics of each setting? For example, given a large collection of retinal images from several different experimental conditions (normal, detached, reattached, etc.), how can data mining help biologists focus on important regions in the images or on the differences between dif... View full abstract»

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  • Adaptive product normalization: using online learning for record linkage in comparison shopping

    Publication Year: 2005
    Cited by:  Papers (14)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (264 KB) | HTML iconHTML

    The problem of record linkage focuses on determining whether two object descriptions refer to the same underlying entity. Addressing this problem effectively has many practical applications, e.g., elimination of duplicate records in databases and citation matching for scholarly articles. In this paper, we consider a new domain where the record linkage problem is manifested: Internet comparison sho... View full abstract»

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  • Using information-theoretic measures to assess association rule interestingness

    Publication Year: 2005
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (336 KB) | HTML iconHTML

    Assessing rules with interestingness measures is the cornerstone of successful applications of association rule discovery. However, there exists no information-theoretic measure which is adapted to the semantics of association rules. In this article, we present the directed information ratio (DIE), a new rule interestingness measure which is based on information theory. DIR is specially designed f... View full abstract»

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  • Shortest-path kernels on graphs

    Publication Year: 2005
    Cited by:  Papers (77)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (168 KB) | HTML iconHTML

    Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels are either computationally expensive or limit... View full abstract»

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  • Mining frequent spatio-temporal sequential patterns

    Publication Year: 2005
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB) | HTML iconHTML

    Many applications track the movement of mobile objects, which can be represented as sequences of timestamped locations. Given such a spatiotemporal series, we study the problem of discovering sequential patterns, which are routes frequently followed by the object. Sequential pattern mining algorithms for transaction data are not directly applicable for this setting. The challenges to address are: ... View full abstract»

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