2014 IEEE International Conference on Data Mining Workshop

14-14 Dec. 2014

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  • [Front cover]

    Publication Year: 2014, Page(s): C4
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  • [Title page i]

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  • [Title page iii]

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  • [Copyright notice]

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  • Table of Contents

    Publication Year: 2014, Page(s):v - xvi
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  • Message from the Conference Chairs

    Publication Year: 2014, Page(s):xvii - xviii
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  • Message from the Workshop Co-Chairs

    Publication Year: 2014, Page(s):xix - xx
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  • Preface to OEDM 2014

    Publication Year: 2014, Page(s):xxi - xxii
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  • Preface to BioDM 2014

    Publication Year: 2014, Page(s):xxiii - xxvi
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  • Preface to DDDM 2014

    Publication Year: 2014, Page(s):xxvii - xxviii
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  • Preface to DMS 2014

    Publication Year: 2014, Page(s):xxix - xxx
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  • Preface to SENTIRE 2014

    Publication Year: 2014, Page(s): xxxi
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  • Preface to MoDAT 2014

    Publication Year: 2014, Page(s):xxxii - xxxiii
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  • Preface to DaMNet 2014

    Publication Year: 2014, Page(s):xxxiv - xxxv
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  • Preface to HDM 2014

    Publication Year: 2014, Page(s):xxxvi - xxxvii
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  • Preface to IClaNov 2014

    Publication Year: 2014, Page(s):xxxviii - xl
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  • Preface to DMBIH 2014

    Publication Year: 2014, Page(s):xli - xlii
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  • Preface to BASNA 2014

    Publication Year: 2014, Page(s):xliii - xliv
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  • Preface to SoftwareMining-2014

    Publication Year: 2014, Page(s):xlv - xlvi
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  • Preface to IDP 2014

    Publication Year: 2014, Page(s):xlvii - xlviii
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  • Preface to DMMI 2014

    Publication Year: 2014, Page(s):xlvix - li
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  • Preface to SDA 2014

    Publication Year: 2014, Page(s):lii - liii
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  • Preface to DINA 2014

    Publication Year: 2014, Page(s):liv - lvi
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  • Preface to SBDMV 2014

    Publication Year: 2014, Page(s):lvii - lviii
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  • Spatio-Temporal Trajectory Region-of-Interest Mining Using Delaunay Triangulation

    Publication Year: 2014, Page(s):1 - 8
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    Due to the ubiquity of GPS enabled devices and the advances in sensing technologies, trajectory data has become abundant. Regions of interest are important since they describe specific hot-spots within the data that often correlate with domain specific phenomena. Traditional region of interest mining utilises grid based rasters to model space. This suffers from two main problems: hard to determine... View full abstract»

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