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IEEE Transactions on Knowledge and Data Engineering

Issue 4 • Date April 2011

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

    Publication Year: 2011, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2011, Page(s): c2
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  • A Link Analysis Extension of Correspondence Analysis for Mining Relational Databases

    Publication Year: 2011, Page(s):481 - 495
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1008 KB) | HTML iconHTML

    This work introduces a link analysis procedure for discovering relationships in a relational database or a graph, generalizing both simple and multiple correspondence analysis. It is based on a random walk model through the database defining a Markov chain having as many states as elements in the database. Suppose we are interested in analyzing the relationships between some elements (or records) ... View full abstract»

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  • A Personalized Ontology Model for Web Information Gathering

    Publication Year: 2011, Page(s):496 - 511
    Cited by:  Papers (33)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1548 KB) | HTML iconHTML

    As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning... View full abstract»

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  • Answering Frequent Probabilistic Inference Queries in Databases

    Publication Year: 2011, Page(s):512 - 526
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1085 KB) | HTML iconHTML

    Existing solutions for probabilistic inference queries mainly focus on answering a single inference query, but seldom address the issues of efficiently returning results for a sequence of frequent queries, which is more popular and practical in many real applications. In this paper, we mainly study the computation caching and sharing among a sequence of inference queries in databases. The clique t... View full abstract»

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  • Discovering Activities to Recognize and Track in a Smart Environment

    Publication Year: 2011, Page(s):527 - 539
    Cited by:  Papers (59)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1524 KB) | HTML iconHTML

    The machine learning and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track activities that people normally perform as part ... View full abstract»

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  • Effective Navigation of Query Results Based on Concept Hierarchies

    Publication Year: 2011, Page(s):540 - 553
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3064 KB) | HTML iconHTML

    Search queries on biomedical databases, such as PubMed, often return a large number of results, only a small subset of which is relevant to the user. Ranking and categorization, which can also be combined, have been proposed to alleviate this information overload problem. Results categorization for biomedical databases is the focus of this work. A natural way to organize biomedical citations is ac... View full abstract»

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  • Estimating and Enhancing Real-Time Data Service Delays: Control-Theoretic Approaches

    Publication Year: 2011, Page(s):554 - 567
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2454 KB) | HTML iconHTML

    It is essential to process real-time data service requests such as stock quotes and trade transactions in a timely manner using fresh data, which represent the current real-world phenomena such as the stock market status. Users may simply leave when the database service delay is excessive. Also, temporally inconsistent data may give an outdated view of the real-world status. However, supporting th... View full abstract»

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  • Finding Correlated Biclusters from Gene Expression Data

    Publication Year: 2011, Page(s):568 - 584
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2015 KB) | HTML iconHTML

    Extracting biologically relevant information from DNA microarrays is a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been proposed for the analysis of gene expression data, but when analyzing the large and heterogeneous collections of gene expression data, conventional clustering algorithms often cannot produce a satis... View full abstract»

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  • IR-Tree: An Efficient Index for Geographic Document Search

    Publication Year: 2011, Page(s):585 - 599
    Cited by:  Papers (34)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1303 KB) | HTML iconHTML

    Given a geographic query that is composed of query keywords and a location, a geographic search engine retrieves documents that are the most textually and spatially relevant to the query keywords and the location, respectively, and ranks the retrieved documents according to their joint textual and spatial relevances to the query. The lack of an efficient index that can simultaneously handle both t... View full abstract»

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  • Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction

    Publication Year: 2011, Page(s):600 - 611
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1325 KB) | HTML iconHTML

    Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feature extraction. Recently, unlabeled data have been utilized to improve LDA. However, the intrinsic problems of LDA still exist and only the similarity among the unlabeled data is utilized. In this paper, we propose a novel ... View full abstract»

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  • TEXT: Automatic Template Extraction from Heterogeneous Web Pages

    Publication Year: 2011, Page(s):612 - 626
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1538 KB) | HTML iconHTML

    World Wide Web is the most useful source of information. In order to achieve high productivity of publishing, the webpages in many websites are automatically populated by using the common templates with contents. The templates provide readers easy access to the contents guided by consistent structures. However, for machines, the templates are considered harmful since they degrade the accuracy and ... View full abstract»

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  • Text Clustering with Seeds Affinity Propagation

    Publication Year: 2011, Page(s):627 - 637
    Cited by:  Papers (27)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1013 KB) | HTML iconHTML

    Based on an effective clustering algorithm-Affinity Propagation (AP)-we present in this paper a novel semisupervised text clustering algorithm, called Seeds Affinity Propagation (SAP). There are two main contributions in our approach: 1) a new similarity metric that captures the structural information of texts, and 2) a novel seed construction method to improve the semisupervised clustering proces... View full abstract»

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  • Some Remarks on the Paper "semQA: SPARQL with Idempotent Disjunction”

    Publication Year: 2011, Page(s):638 - 639
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (87 KB) | HTML iconHTML

    In the paper, “semQA: SPARQL with Idempotent Disjunction”, the authors study the RDF query language SPARQL. In particular, they claim that some of the results presented in are not correct. In this note, we refute the claims made in, and actually show that some of the formal results of are incorrect. View full abstract»

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  • IEEE and IEEE Computer Society Special Student Offer

    Publication Year: 2011, Page(s): 640
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  • TKDE Information for authors

    Publication Year: 2011, Page(s): c3
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  • [Back cover]

    Publication Year: 2011, 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