Data mining and knowledge discovery

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  Año 2020, Vol. 34, Número 1

  • A semi-supervised model for knowledge graph embedding.

    Jia Zhu, Zetao Zheng, Min Yang, Gabriel Pui Cheong Fung, Yong Tang

    • Resumen

    págs. 1-20

    

  • Interactive visual data exploration with subjective feedback: an information-theoretic approach

    Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, Tijl De Bie

    • Resumen

    págs. 21-49

    

  • A drift detection method based on dynamic classifier selection.

    Felipe Pinagé, Eulanda M. dos Santos, João Gama

    • Resumen

    págs. 50-74

    

  • Topical network embedding.

    Min Shi, Yufei Tang, Xingquan Zhu, Jianxun Liu, Haibo He--

    • Resumen

    págs. 75-100

    

  • Grafting for combinatorial binary model using frequent itemset mining.

    Taito Lee, Shin Matsushima, Kenji Yamanishi

    • Resumen

    págs. 101-123

    

  • A comparative study of data-dependent approaches without learning in measuring similarities of data objects.

    Sunil Aryal, Kai Ming Ting, Takashi Washio, Gholamreza Haffari

    • Resumen

    págs. 124-162

    

  • Matching code and law: achieving algorithmic fairness with optimal transport.

    Meike Zehlike, Philipp Hacker, Emil Wiedemann

    • Resumen

    págs. 163-200

    

  • Deep multi-task learning for individuals origin–destination matrices estimation from census data.

    Mehdi Katranji, Sami Kraiem, Laurent Moalic, Guilhem Sanmarty, Ghazaleh Khodabandelou, Alexandre Caminada, Fouad Hadj Selem

    • Resumen

    págs. 201-230

    

  • FastEE: Fast Ensembles of Elastic Distances for time series classification.

    Chang Wei Tan, François Petitjean, Geoffrey I. Webb

    • Resumen

    págs. 231-272