Complex Pattern Mining

New Challenges, Methods and Applications

  • Annalisa Appice
  • Michelangelo Ceci
  • Corrado Loglisci
  • Giuseppe Manco
  • Elio Masciari
  • Zbigniew W. Ras

Part of the Studies in Computational Intelligence book series (SCI, volume 880)

Table of contents

  1. Front Matter
    Pages i-x
  2. Yifeng Lu, Florian Richter, Thomas Seidl
    Pages 1-16
  3. Zhao Xu, Lorenzo von Ritter, Giuseppe Serra
    Pages 17-32
  4. Alicja Wieczorkowska, Wojciech Jarmulski
    Pages 33-45
  5. Nyoman Juniarta, Miguel Couceiro, Amedeo Napoli
    Pages 47-62
  6. Pasquale Ardimento, Nicola Boffoli, Costantino Mele
    Pages 63-83
  7. Evis Trandafili, Elinda Kajo Meçe, Enea Duka
    Pages 85-101
  8. Laura Genga, Domenico Potena, Andrea Chiorrini, Claudia Diamantini, Nicola Zannone
    Pages 103-119
  9. Stefano Ferilli, Sergio Angelastro
    Pages 121-136
  10. Angelo Impedovo, Corrado Loglisci, Michelangelo Ceci, Donato Malerba
    Pages 137-152
  11. Giuseppina Andresini, Annalisa Appice, Donato Malerba
    Pages 173-187
  12. Laurel Powell, Anna Gelich, Zbigniew W. Ras
    Pages 189-211
  13. Nicola Fiorentino, Cristian Molinaro, Irina Trubitsyna
    Pages 213-227
  14. Antonio Angrisano, Pasquale Ardimento, Mario Luca Bernardi, Marta Cimitile, Salvatore Gaglione
    Pages 229-247
  15. Back Matter
    Pages 249-250

About this book


This book discusses the challenges facing current research in knowledge discovery and data mining posed by the huge volumes of complex data now gathered in various real-world applications (e.g., business process monitoring, cybersecurity, medicine, language processing, and remote sensing). The book consists of 14 chapters covering the latest research by the authors and the research centers they represent. It illustrates techniques and algorithms that have recently been developed to preserve the richness of the data and allow us to efficiently and effectively identify the complex information it contains. Presenting the latest developments in complex pattern mining, this book is a valuable reference resource for data science researchers and professionals in academia and industry.


Complex Pattern Mining NFMCP Representation Formalisms Pattern Discovery Foundations of Pattern Mining Mining Dynamic Data Mining Evolving Data

Editors and affiliations

  1. 1.Dipartimento di InformaticaUniversità degli Studi di Bari Aldo MoroBariItaly
  2. 2.Dipartimento di InformaticaUniversità degli Studi di Bari Aldo MoroBariItaly
  3. 3.Dipartimento di InformaticaUniversità degli Studi di Bari Aldo MoroBariItaly
  4. 4.ICAR-CNRRendeItaly
  5. 5.Università degli Studi di Napoli Federico IINaplesItaly
  6. 6.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA

Bibliographic information