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Network reconstruction from dynamic data

Published:01 December 2006Publication History
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Abstract

Over the past decade, many powerful data mining techniques have been developed to analyze temporal and sequential data. The time is now fertile for addressing problems of larger scope under the purview of temporal data mining. The fourth SIGKDD workshop on temporal data mining focused on the question: What can we infer about the structure of a complex dynamical system from observed temporal data? The goals of the workshop were to critically evaluate the need in this area by bringing together leading researchers from industry and academia, and to identify promising technologies and methodologies for doing the same. We provide a brief summary of the workshop proceedings and ideas arising out of the discussions.

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  1. Network reconstruction from dynamic data

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        cover image ACM SIGKDD Explorations Newsletter
        ACM SIGKDD Explorations Newsletter  Volume 8, Issue 2
        December 2006
        106 pages
        ISSN:1931-0145
        EISSN:1931-0153
        DOI:10.1145/1233321
        Issue’s Table of Contents

        Copyright © 2006 Authors

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 December 2006

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