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Knowledge and Data Engineering, IEEE Transactions on

Issue 3 • Date March 2012

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Displaying Results 1 - 20 of 20
  • [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 Similarity Search of Time Series Cliques with Natural Relations

    Publication Year: 2012 , Page(s): 385 - 398
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1467 KB) |  | HTML iconHTML  

    A Time Series Clique (TSC) consists of multiple time series which are related to each other by natural relations. The natural relations that are found between the time series depend on the application domains. For example, a TSC can consist of time series which are trajectories in video that have spatial relations. In conventional time series retrieval, such natural relations between the time seri... View full abstract»

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  • A Genetic Programming Approach to Record Deduplication

    Publication Year: 2012 , Page(s): 399 - 412
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1373 KB) |  | HTML iconHTML  

    Several systems that rely on consistent data to offer high-quality services, such as digital libraries and e-commerce brokers, may be affected by the existence of duplicates, quasi replicas, or near-duplicate entries in their repositories. Because of that, there have been significant investments from private and government organizations for developing methods for removing replicas from its data re... View full abstract»

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  • A Link-Based Cluster Ensemble Approach for Categorical Data Clustering

    Publication Year: 2012 , Page(s): 413 - 425
    Cited by:  Papers (7)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1447 KB) |  | HTML iconHTML  

    Although attempts have been made to solve the problem of clustering categorical data via cluster ensembles, with the results being competitive to conventional algorithms, it is observed that these techniques unfortunately generate a final data partition based on incomplete information. The underlying ensemble-information matrix presents only cluster-data point relations, with many entries being le... View full abstract»

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  • A Probabilistic Scheme for Keyword-Based Incremental Query Construction

    Publication Year: 2012 , Page(s): 426 - 439
    Cited by:  Patents (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1353 KB) |  | HTML iconHTML  

    Databases enable users to precisely express their informational needs using structured queries. However, database query construction is a laborious and error-prone process, which cannot be performed well by most end users. Keyword search alleviates the usability problem at the price of query expressiveness. As keyword search algorithms do not differentiate between the possible informational needs ... View full abstract»

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  • Efficiently Indexing Large Sparse Graphs for Similarity Search

    Publication Year: 2012 , Page(s): 440 - 451
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2647 KB) |  | HTML iconHTML  

    The graph structure is a very important means to model schemaless data with complicated structures, such as protein-protein interaction networks, chemical compounds, knowledge query inferring systems, and road networks. This paper focuses on the index structure for similarity search on a set of large sparse graphs and proposes an efficient indexing mechanism by introducing the Q-Gram idea. By deco... View full abstract»

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  • Extending Attribute Information for Small Data Set Classification

    Publication Year: 2012 , Page(s): 452 - 464
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1452 KB) |  | HTML iconHTML  

    Data quantity is the main issue in the small data set problem, because usually insufficient data will not lead to a robust classification performance. How to extract more effective information from a small data set is thus of considerable interest. This paper proposes a new attribute construction approach which converts the original data attributes into a higher dimensional feature space to extrac... View full abstract»

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  • Feature Selection Based on Class-Dependent Densities for High-Dimensional Binary Data

    Publication Year: 2012 , Page(s): 465 - 477
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2065 KB) |  | HTML iconHTML  

    Data and knowledge management systems employ feature selection algorithms for removing irrelevant, redundant, and noisy information from the data. There are two well-known approaches to feature selection, feature ranking (FR) and feature subset selection (FSS). In this paper, we propose a new FR algorithm, termed as class-dependent density-based feature elimination (CDFE), for binary data sets. Ou... View full abstract»

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  • Learning Bregman Distance Functions for Semi-Supervised Clustering

    Publication Year: 2012 , Page(s): 478 - 491
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2901 KB)  

    Learning distance functions with side information plays a key role in many data mining applications. Conventional distance metric learning approaches often assume that the target distance function is represented in some form of Mahalanobis distance. These approaches usually work well when data are in low dimensionality, but often become computationally expensive or even infeasible when handling hi... View full abstract»

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  • Measuring the Sky: On Computing Data Cubes via Skylining the Measures

    Publication Year: 2012 , Page(s): 492 - 505
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1684 KB) |  | HTML iconHTML  

    Data cube is a key element in supporting fast OLAP. Traditionally, an aggregate function is used to compute the values in data cubes. In this paper, we extend the notion of data cubes with a new perspective. Instead of using an aggregate function, we propose to build data cubes using the skyline operation as the “aggregate function.” Data cubes built in this way are called “gr... View full abstract»

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  • On the Complexity of View Update Analysis and Its Application to Annotation Propagation

    Publication Year: 2012 , Page(s): 506 - 519
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1095 KB) |  | HTML iconHTML  

    This paper investigates three problems identified in [1] for annotation propagation, namely, the view side-effect, source side-effect, and annotation placement problems. Given annotations entered for a tuple or an attribute in a view, these problems ask what tuples or attributes in the source have to be annotated to produce the view annotations. As observed in [1], these problems are fundamental n... View full abstract»

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  • Publishing Search Logs—A Comparative Study of Privacy Guarantees

    Publication Year: 2012 , Page(s): 520 - 532
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1738 KB) |  | HTML iconHTML  

    Search engine companies collect the “database of intentions,” the histories of their users' search queries. These search logs are a gold mine for researchers. Search engine companies, however, are wary of publishing search logs in order not to disclose sensitive information. In this paper, we analyze algorithms for publishing frequent keywords, queries, and clicks of a search log. We... View full abstract»

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  • Resilient Identity Crime Detection

    Publication Year: 2012 , Page(s): 533 - 546
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1074 KB) |  | HTML iconHTML  

    Identity crime is well known, prevalent, and costly; and credit application fraud is a specific case of identity crime. The existing nondata mining detection system of business rules and scorecards, and known fraud matching have limitations. To address these limitations and combat identity crime in real time, this paper proposes a new multilayered detection system complemented with two additional ... View full abstract»

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  • ROAD: A New Spatial Object Search Framework for Road Networks

    Publication Year: 2012 , Page(s): 547 - 560
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1607 KB) |  | HTML iconHTML  

    In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for L... View full abstract»

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  • Slicing: A New Approach for Privacy Preserving Data Publishing

    Publication Year: 2012 , Page(s): 561 - 574
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1441 KB) |  | HTML iconHTML  

    Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that generalization loses considerable amount of information, especially for high-dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation b... View full abstract»

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  • TKDE Seeks Applications for EIC for 2013-2014 Term

    Publication Year: 2012 , Page(s): 575
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    Freely Available from IEEE
  • IEEE Computer Society OnlinePlus Coming Soon to TKDE

    Publication Year: 2012 , Page(s): 576
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    Freely Available from IEEE
  • [Cover3]

    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