High Utility Pattern Mining Theory Algorithms and Applications 1st Edition by Philippe Fournier Viger, Jerry Chun Wei Lin, Roger Nkambou, Bay Vo, Vincent S Tseng ISBN 9783030049201 3030049205

High-Utility Pattern Mining: Theory, Algorithms and Applications 1st Edition by Philippe Fournier-Viger, Jerry Chun-Wei Lin, Roger Nkambou, Bay Vo, Vincent S. Tseng – Ebook PDF Instant Download/Delivery: 9783030049201, 3030049205

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Product details:

ISBN 10: 3030049205

ISBN 13:  9783030049201

Author:  Philippe Fournier-Viger, Jerry Chun-Wei Lin, Roger Nkambou, Bay Vo, Vincent S. Tseng

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, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data.

The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.

Table of contents: 

1. A Survey of High Utility Itemset Mining

2. A Comparative Study of Top-K High Utility Itemset Mining Methods

3. A Survey of High Utility Pattern Mining Algorithms for Big Data

4. A Survey of High Utility Sequential Pattern Mining

5. Efficient Algorithms for High Utility Itemset Mining Without Candidate Generation

6. High Utility Association Rule Mining

7. Mining High-Utility Irregular Itemsets

8. A Survey of Privacy Preserving Utility Mining

9. Extracting Potentially High Profit Product Feature Groups by Using High Utility Pattern Mining and Aspect Based Sentiment Analysis

10. Metaheuristics for Frequent and High-Utility Itemset Mining

11. Mining Compact High Utility Itemsets Without Candidate Generation

12. Visualization and Visual Analytic Techniques for Patterns

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Tags: Philippe Fournier Viger, Jerry Chun Wei Lin, Roger Nkambou, Bay Vo, Vincent S Tseng, High Utility, Pattern Mining, Theory, Algorithms, Applications