Complex Pattern Mining
New Challenges, Methods and Applications
Published on 14. January 2020
X, 250 pages
978-3-030-36617-9 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
X, 250 p. 77 illus., 47 illus. in color.
File size
9,10 MB
ISBN-13
978-3-030-36617-9 (9783030366179)
DOI
10.1007/978-3-030-36617-9
Schweitzer Classification
Other editions
Additional editions
Annalisa Appice | Michelangelo Ceci | Corrado Loglisci
Complex Pattern Mining
New Challenges, Methods and Applications
Book
01/2020
Springer
€181.89
Shipment within 7-9 days
Persons
Content
E?cient Infrequent Pattern Mining using Negative Itemset Tree.- Hierarchical Adversarial Training for Multi-Domain.- Optimizing C-index via Gradient Boosting in Medical Survival Analysis.- Order-preserving Biclustering Based on FCA and Pattern Structures.- A text-based regression approach to predict bug-?x time.- A Named Entity Recognition Approach for Albanian Using Deep Learning.- A Latitudinal Study on the Use of Sequential and Concurrency Patterns in Deviance Mining.- E?cient Declarative-based Process Mining using an Enhanced Framework.- Exploiting Pattern Set Dissimilarity for Detecting Changes in Communication Networks.- Classi?cation and Clustering of Emotive Microblogs in Albanian: Two User-Oriented Tasks.
