Advanced analysis and learning on te...
Clark Conference ((2005 :)

 

  • Advanced analysis and learning on temporal data[electronic resource] :first ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015 : revised selected papers /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    杜威分類號: 519.55
    書名/作者: Advanced analysis and learning on temporal data : first ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015 : revised selected papers // edited by Ahlame Douzal-Chouakria, Jose A. Vilar, Pierre-Francois Marteau.
    其他題名: AALTD 2015
    其他作者: Douzal-Chouakria, Ahlame.
    團體作者: Clark Conference
    出版者: Cham : : Springer International Publishing :, 2016.
    面頁冊數: x, 173 p. : : ill., digital ;; 24 cm.
    Contained By: Springer eBooks
    標題: Time-series analysis - Congresses. - Data processing
    標題: Machine learning
    標題: Temporal databases
    標題: Computer Science.
    標題: Artificial Intelligence (incl. Robotics)
    標題: Database Management.
    標題: Information Systems Applications (incl. Internet)
    標題: Information Storage and Retrieval.
    標題: Algorithm Analysis and Problem Complexity.
    ISBN: 9783319444123
    ISBN: 9783319444116
    摘要、提要註: This book constitutes the refereed proceedings of the First ECML PKDD Workshop, AALTD 2015, held in Porto, Portugal, in September 2016. The 11 full papers presented were carefully reviewed and selected from 22 submissions. The first part focuses on learning new representations and embeddings for time series classification, clustering or for dimensionality reduction. The second part presents approaches on classification and clustering with challenging applications on medicine or earth observation data. These works show different ways to consider temporal dependency in clustering or classification processes. The last part of the book is dedicated to metric learning and time series comparison, it addresses the problem of speeding-up the dynamic time warping or dealing with multi-modal and multi-scale metric learning for time series classification and clustering.
    電子資源: http://dx.doi.org/10.1007/978-3-319-44412-3
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