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IEEE Transactions on Knowledge and Data Engineering

Issue 7 • Date July 2011

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Displaying Results 1 - 18 of 18
  • [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 Hidden Topic-Based Framework toward Building Applications with Short Web Documents

    Publication Year: 2011, Page(s):961 - 976
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (7057 KB) | HTML iconHTML Multimedia Media

    This paper introduces a hidden topic-based framework for processing short and sparse documents (e.g., search result snippets, product descriptions, book/movie summaries, and advertising messages) on the Web. The framework focuses on solving two main challenges posed by these kinds of documents: 1) data sparseness and 2) synonyms/homonyms. The former leads to the lack of shared words and contexts a... View full abstract»

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  • A Web Search Engine-Based Approach to Measure Semantic Similarity between Words

    Publication Year: 2011, Page(s):977 - 990
    Cited by:  Papers (61)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1562 KB) | HTML iconHTML

    Measuring the semantic similarity between words is an important component in various tasks on the web such as relation extraction, community mining, document clustering, and automatic metadata extraction. Despite the usefulness of semantic similarity measures in these applications, accurately measuring semantic similarity between two words (or entities) remains a challenging task. We propose an em... View full abstract»

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  • Flexible and Efficient Resolution of Skyline Query Size Constraints

    Publication Year: 2011, Page(s):991 - 1005
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1694 KB) | HTML iconHTML

    Given a set of multidimensional points, a skyline query returns the interesting points that are not dominated by other points. It has been observed that the actual cardinality (s) of a skyline query result may differ substantially from the desired result cardinality (k), which has prompted studies on how to reduce s for the case where k<;s. This paper goes further by addressing the general case... View full abstract»

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  • Graph Pattern Matching: A Join/Semijoin Approach

    Publication Year: 2011, Page(s):1006 - 1021
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1651 KB) | HTML iconHTML

    Due to rapid growth of the Internet and new scientific/technological advances, there exist many new applications that model data as graphs, because graphs have sufficient expressiveness to model complicated structures. The dominance of graphs in real-world applications demands new graph processing techniques to access large data graphs effectively and efficiently. In this paper, we study a graph p... View full abstract»

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  • Higher Order Naïve Bayes: A Novel Non-IID Approach to Text Classification

    Publication Year: 2011, Page(s):1022 - 1034
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1442 KB) | HTML iconHTML

    The underlying assumption in traditional machine learning algorithms is that instances are Independent and Identically Distributed (IID). These critical independence assumptions made in traditional machine learning algorithms prevent them from going beyond instance boundaries to exploit latent relations between features. In this paper, we develop a general approach to supervised learning by levera... View full abstract»

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  • KEMB: A Keyword-Based XML Message Broker

    Publication Year: 2011, Page(s):1035 - 1049
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2332 KB) | HTML iconHTML

    This paper studies the problem of XML message brokering with user subscribed profiles of keyword queries and presents a KEyword-based XML Message Broker (KEMB) to address this problem. In contrast to traditional-path-expressions-based XML message brokers, KEMB stores a large number of user profiles, in the form of keyword queries, which capture the data requirement of users/applications, as oppose... View full abstract»

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  • myOLAP: An Approach to Express and Evaluate OLAP Preferences

    Publication Year: 2011, Page(s):1050 - 1064
    Cited by:  Papers (7)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1858 KB) | HTML iconHTML Multimedia Media

    Multidimensional databases are the core of business intelligence systems. Their users express complex OLAP queries, often returning large volumes of facts, sometimes providing little or no information. Thus, expressing preferences could be highly valuable in this domain. The OLAP domain is representative of an unexplored class of preference queries, characterized by three peculiarities: preference... View full abstract»

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  • Processing of Continuous Location-Based Range Queries on Moving Objects in Road Networks

    Publication Year: 2011, Page(s):1065 - 1078
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1182 KB) | HTML iconHTML

    With the proliferation of mobile devices, an increasing number of urban users subscribe to location-based services. This trend has led to significant research interest in techniques that address two fundamental requirements: road network-based distance computation and the capability to process moving objects as points of interests. However, there exist few techniques that support both requirements... View full abstract»

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  • Random k-Labelsets for Multilabel Classification

    Publication Year: 2011, Page(s):1079 - 1089
    Cited by:  Papers (109)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1436 KB) | HTML iconHTML

    A simple yet effective multilabel learning method, called label powerset (LP), considers each distinct combination of labels that exist in the training set as a different class value of a single-label classification task. The computational efficiency and predictive performance of LP is challenged by application domains with large number of labels and training examples. In these cases, the number o... View full abstract»

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  • Reducing the Loss of Information through Annealing Text Distortion

    Publication Year: 2011, Page(s):1090 - 1102
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1820 KB) | HTML iconHTML

    Compression distances have been widely used in knowledge discovery and data mining. They are parameter-free, widely applicable, and very effective in several domains. However, little has been done to interpret their results or to explain their behavior. In this paper, we take a step toward understanding compression distances by performing an experimental evaluation of the impact of several kinds o... View full abstract»

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  • Trace-Oriented Feature Analysis for Large-Scale Text Data Dimension Reduction

    Publication Year: 2011, Page(s):1103 - 1117
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2291 KB) | HTML iconHTML

    Dimension reduction for large-scale text data is attracting much attention nowadays due to the rapid growth of the World Wide Web. We can categorize those popular dimension reduction algorithms into two groups: feature extraction and feature selection algorithms. In the former, new features are combined from their original features through algebraic transformation. Though many of them have been va... View full abstract»

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  • CPS Handles the Details for you [advertisement]

    Publication Year: 2011, Page(s): 1118
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  • IEEE and IEEE Computer Society Special Student Offer

    Publication Year: 2011, Page(s): 1119
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  • Stay Connected with the IEEE Computer Society [advertisement]

    Publication Year: 2011, Page(s): 1120
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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