By Topic

Knowledge and Data Engineering, IEEE Transactions on

Issue 1 • Date Jan. 2006

Filter Results

Displaying Results 1 - 17 of 17
  • [Front cover]

    Publication Year: 2006 , Page(s): c1
    Save to Project icon | Request Permissions | PDF file iconPDF (132 KB)  
    Freely Available from IEEE
  • [Inside front cover]

    Publication Year: 2006 , Page(s): c2
    Save to Project icon | Request Permissions | PDF file iconPDF (89 KB)  
    Freely Available from IEEE
  • EIC Editorial: State of the Transactions

    Publication Year: 2006 , Page(s): 1 - 5
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | PDF file iconPDF (184 KB)  
    Freely Available from IEEE
  • Text classification without negative examples revisit

    Publication Year: 2006 , Page(s): 6 - 20
    Cited by:  Papers (31)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2472 KB) |  | HTML iconHTML  

    Traditionally, building a classifier requires two sets of examples: positive examples and negative examples. This paper studies the problem of building a text classifier using positive examples (P) and unlabeled examples (U). The unlabeled examples are mixed with both positive and negative examples. Since no negative example is given explicitly, the task of building a reliable text classifier beco... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fast and memory efficient mining of frequent closed itemsets

    Publication Year: 2006 , Page(s): 21 - 36
    Cited by:  Papers (35)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1680 KB) |  | HTML iconHTML  

    This paper presents a new scalable algorithm for discovering closed frequent itemsets, a lossless and condensed representation of all the frequent itemsets that can be mined from a transactional database. Our algorithm exploits a divide-and-conquer approach and a bitwise vertical representation of the database and adopts a particular visit and partitioning strategy of the search space based on an ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Input variable selection: mutual information and linear mixing measures

    Publication Year: 2006 , Page(s): 37 - 46
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (760 KB) |  | HTML iconHTML  

    Determining the most appropriate inputs to a model has a significant impact on the performance of the model and associated algorithms for classification, prediction, and data analysis. Previously, we proposed an algorithm ICAIVS which utilizes independent component analysis (ICA) as a preprocessing stage to overcome issues of dependencies between inputs, before the data being passed through to an ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A new complicated-knowledge representation approach based on knowledge meshes

    Publication Year: 2006 , Page(s): 47 - 62
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1016 KB) |  | HTML iconHTML  

    This paper presents a new complicated-knowledge representation method for the self-reconfiguration of complex systems such as complex software systems, complex manufacturing systems, and knowledgeable manufacturing systems. Herein, new concepts of a knowledge mesh (KM) and an agent mesh (AM) are proposed along with a new KM-based approach to complicated-knowledge representation. KM is the represen... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Training cost-sensitive neural networks with methods addressing the class imbalance problem

    Publication Year: 2006 , Page(s): 63 - 77
    Cited by:  Papers (130)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (3360 KB) |  | HTML iconHTML  

    This paper studies empirically the effect of sampling and threshold-moving in training cost-sensitive neural networks. Both oversampling and undersampling are considered. These techniques modify the distribution of the training data such that the costs of the examples are conveyed explicitly by the appearances of the examples. Threshold-moving tries to move the output threshold toward inexpensive ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Range nearest-neighbor query

    Publication Year: 2006 , Page(s): 78 - 91
    Cited by:  Papers (22)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (920 KB) |  | HTML iconHTML  

    A range nearest-neighbor (RNN) query retrieves the nearest neighbor (NN) for every point in a range. It is a natural generalization of point and continuous nearest-neighbor queries and has many applications. In this paper, we consider the ranges as (hyper)rectangles and propose efficient in-memory processing and secondary memory pruning techniques for RNN queries in both 2D and high-dimensional sp... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Random projection-based multiplicative data perturbation for privacy preserving distributed data mining

    Publication Year: 2006 , Page(s): 92 - 106
    Cited by:  Papers (83)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (992 KB) |  | HTML iconHTML  

    This paper explores the possibility of using multiplicative random projection matrices for privacy preserving distributed data mining. It specifically considers the problem of computing statistical aggregates like the inner product matrix, correlation coefficient matrix, and Euclidean distance matrix from distributed privacy sensitive data possibly owned by multiple parties. This class of problems... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Link contexts in classifier-guided topical crawlers

    Publication Year: 2006 , Page(s): 107 - 122
    Cited by:  Papers (25)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1456 KB) |  | HTML iconHTML  

    Context of a hyperlink or link context is defined as the terms that appear in the text around a hyperlink within a Web page. Link contexts have been applied to a variety of Web information retrieval and categorization tasks. Topical or focused Web crawlers have a special reliance on link contexts. These crawlers automatically navigate the hyperlinked structure of the Web while using link contexts ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • MALLET - a multi-agent logic language for encoding teamwork

    Publication Year: 2006 , Page(s): 123 - 138
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (904 KB) |  | HTML iconHTML  

    MALLET, a multi-agent logic language for encoding teamwork, is intended to enable expression of teamwork emulating human teamwork, allowing experimentation with different levels and forms of inferred team intelligence. A consequence of this goal is that the actual teamwork behavior is determined by the level of intelligence built into the underlying system as well as the semantics of the language.... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • 2005 Reviewers List

    Publication Year: 2006 , Page(s): 139 - 142
    Save to Project icon | Request Permissions | PDF file iconPDF (57 KB)  
    Freely Available from IEEE
  • Call for Papers for Special Issue on Customer Relationship Management: Data Mining Meets Marketing

    Publication Year: 2006 , Page(s): 143
    Save to Project icon | Request Permissions | PDF file iconPDF (39 KB)  
    Freely Available from IEEE
  • [Advertisement]

    Publication Year: 2006 , Page(s): 144
    Save to Project icon | Request Permissions | PDF file iconPDF (354 KB)  
    Freely Available from IEEE
  • TKDE Information for authors

    Publication Year: 2006 , Page(s): c3
    Save to Project icon | Request Permissions | PDF file iconPDF (89 KB)  
    Freely Available from IEEE
  • [Back cover]

    Publication Year: 2006 , Page(s): c4
    Save to Project icon | Request Permissions | PDF file iconPDF (132 KB)  
    Freely Available from IEEE

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