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IEEE Transactions on Knowledge and Data Engineering

Issue 6 • Date June 2012

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Displaying Results 1 - 21 of 21
  • [Front cover]

    Publication Year: 2012, Page(s): c1
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  • [Inside front cover]

    Publication Year: 2012, Page(s): c2
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  • A Knowledge-Driven Approach to Activity Recognition in Smart Homes

    Publication Year: 2012, Page(s):961 - 974
    Cited by:  Papers (74)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1305 KB) | HTML iconHTML

    This paper introduces a knowledge-driven approach to real-time, continuous activity recognition based on multisensor data streams in smart homes. The approach goes beyond the traditional data-centric methods for activity recognition in three ways. First, it makes extensive use of domain knowledge in the life cycle of activity recognition. Second, it uses ontologies for explicit context and activit... View full abstract»

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  • A Unified Probabilistic Framework for Name Disambiguation in Digital Library

    Publication Year: 2012, Page(s):975 - 987
    Cited by:  Papers (31)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2085 KB) | HTML iconHTML

    Despite years of research, the name ambiguity problem remains largely unresolved. Outstanding issues include how to capture all information for name disambiguation in a unified approach, and how to determine the number of people K in the disambiguation process. In this paper, we formalize the problem in a unified probabilistic framework, which incorporates both attributes and relationships. Specif... View full abstract»

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  • Clustering with Multiviewpoint-Based Similarity Measure

    Publication Year: 2012, Page(s):988 - 1001
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1918 KB) | HTML iconHTML

    All clustering methods have to assume some cluster relationship among the data objects that they are applied on. Similarity between a pair of objects can be defined either explicitly or implicitly. In this paper, we introduce a novel multiviewpoint-based similarity measure and two related clustering methods. The major difference between a traditional dissimilarity/similarity measure and ours is th... View full abstract»

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  • Document Clustering in Correlation Similarity Measure Space

    Publication Year: 2012, Page(s):1002 - 1013
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3244 KB) | HTML iconHTML

    This paper presents a new spectral clustering method called correlation preserving indexing (CPI), which is performed in the correlation similarity measure space. In this framework, the documents are projected into a low-dimensional semantic space in which the correlations between the documents in the local patches are maximized while the correlations between the documents outside these patches ar... View full abstract»

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  • Efficient Extended Boolean Retrieval

    Publication Year: 2012, Page(s):1014 - 1024
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (976 KB) | HTML iconHTML

    Extended Boolean retrieval (EBR) models were proposed nearly three decades ago, but have had little practical impact, despite their significant advantages compared to either ranked keyword or pure Boolean retrieval. In particular, EBR models produce meaningful rankings; their query model allows the representation of complex concepts in an and-or format; and they are scrutable, in that the score as... View full abstract»

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  • Locally Discriminative Coclustering

    Publication Year: 2012, Page(s):1025 - 1035
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1067 KB) | HTML iconHTML

    Different from traditional one-sided clustering techniques, coclustering makes use of the duality between samples and features to partition them simultaneously. Most of the existing co-clustering algorithms focus on modeling the relationship between samples and features, whereas the intersample and interfeature relationships are ignored. In this paper, we propose a novel coclustering algorithm nam... View full abstract»

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  • Low-Rank Kernel Matrix Factorization for Large-Scale Evolutionary Clustering

    Publication Year: 2012, Page(s):1036 - 1050
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1671 KB) | HTML iconHTML

    Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorithm to adapt to the recent changes in the evolving data, but it also needs to take the historical relationship between the data points into consideration. In this paper, we propose ECKF, a general framework for evolutionary c... View full abstract»

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  • Mining Web Graphs for Recommendations

    Publication Year: 2012, Page(s):1051 - 1064
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1935 KB) | HTML iconHTML

    As the exponential explosion of various contents generated on the Web, Recommendation techniques have become increasingly indispensable. Innumerable different kinds of recommendations are made on the Web every day, including movies, music, images, books recommendations, query suggestions, tags recommendations, etc. No matter what types of data sources are used for the recommendations, essentially ... View full abstract»

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  • Query Planning for Continuous Aggregation Queries over a Network of Data Aggregators

    Publication Year: 2012, Page(s):1065 - 1079
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (862 KB) | HTML iconHTML Multimedia Media

    Continuous queries are used to monitor changes to time varying data and to provide results useful for online decision making. Typically a user desires to obtain the value of some aggregation function over distributed data items, for example, to know value of portfolio for a client; or the AVG of temperatures sensed by a set of sensors. In these queries a client specifies a coherency requirement as... View full abstract»

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  • Scalable Learning of Collective Behavior

    Publication Year: 2012, Page(s):1080 - 1091
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1894 KB) | HTML iconHTML Multimedia Media

    This study of collective behavior is to understand how individuals behave in a social networking environment. Oceans of data generated by social media like Facebook, Twitter, Flickr, and YouTube present opportunities and challenges to study collective behavior on a large scale. In this work, we aim to learn to predict collective behavior in social media. In particular, given information about some... View full abstract»

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  • Scalable Scheduling of Updates in Streaming Data Warehouses

    Publication Year: 2012, Page(s):1092 - 1105
    Cited by:  Papers (4)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (883 KB) | HTML iconHTML

    We discuss update scheduling in streaming data warehouses, which combine the features of traditional data warehouses and data stream systems. In our setting, external sources push append-only data streams into the warehouse with a wide range of interarrival times. While traditional data warehouses are typically refreshed during downtimes, streaming warehouses are updated as new data arrive. We mod... View full abstract»

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  • Using Rule Ontology in Repeated Rule Acquisition from Similar Web Sites

    Publication Year: 2012, Page(s):1106 - 1119
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2736 KB) | HTML iconHTML

    Inferential rules are as essential to the Semantic Web applications as ontology. Therefore, rule acquisition is also an important issue, and the Web that implies inferential rules can be a major source of rule acquisition. We expect that it will be easier to acquire rules from a site by using similar rules of other sites in the same domain rather than starting from scratch. We proposed an automati... View full abstract»

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  • Visual Role Mining: A Picture Is Worth a Thousand Roles

    Publication Year: 2012, Page(s):1120 - 1133
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1678 KB) | HTML iconHTML

    This paper offers a new role engineering approach to Role-Based Access Control (RBAC), referred to as visual role mining. The key idea is to graphically represent user-permission assignments to enable quick analysis and elicitation of meaningful roles. First, we formally define the problem by introducing a metric for the quality of the visualization. Then, we prove that finding the best representa... View full abstract»

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  • Weakly Supervised Joint Sentiment-Topic Detection from Text

    Publication Year: 2012, Page(s):1134 - 1145
    Cited by:  Papers (34)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1414 KB) | HTML iconHTML

    Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the JS... View full abstract»

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  • Software Fault Prediction Using Quad Tree-Based K-Means Clustering Algorithm

    Publication Year: 2012, Page(s):1146 - 1150
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1038 KB)

    Unsupervised techniques like clustering may be used for fault prediction in software modules, more so in those cases where fault labels are not available. In this paper a Quad Tree-based K-Means algorithm has been applied for predicting faults in program modules. The aims of this paper are twofold. First, Quad Trees are applied for finding the initial cluster centers to be input to the A'-Means Al... View full abstract»

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  • What's new in Transactions [advertisement]

    Publication Year: 2012, Page(s): 1151
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  • Stay Connected with the IEEE Computer Society [advertisement]

    Publication Year: 2012, Page(s): 1152
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  • [Inside back cover]

    Publication Year: 2012, Page(s): c3
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  • [Back cover]

    Publication Year: 2012, Page(s): c4
    Request permission for commercial reuse | PDF file iconPDF (133 KB)
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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