High-Utility Pattern Mining Theory, Algorithms and Applications /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Fournier-Viger, Philippe (Editor, http://id.loc.gov/vocabulary/relators/edt), Lin, Jerry Chun-Wei (Editor, http://id.loc.gov/vocabulary/relators/edt), Nkambou, Roger (Editor, http://id.loc.gov/vocabulary/relators/edt), Vo, Bay (Editor, http://id.loc.gov/vocabulary/relators/edt), Tseng, Vincent S. (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Studies in Big Data, 51
• Subjects: Computational intelligence.; Artificial intelligence.; Data mining.; Computational Intelligence.; Artificial Intelligence.; Data Mining and Knowledge Discovery.

This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications,...

Table of Contents:

• Introduction
• Problem Definition
• Algorithms
• Extensions of the Problem
• Research Opportunities
• Open-Source Implementations
• Conclusion.