Periodic Pattern Mining: Theory, Algorithms, and Applications
暫譯: 週期性模式挖掘：理論、演算法與應用

Rage, Uday Kiran, Fournier-Viger, Philippe, Luna, Jose Maria

Periodic Pattern Mining: Theory, Algorithms, and Applications
  • 出版商: Springer
  • 出版日期: 2021-10-30
  • 售價: $6,720
  • 貴賓價: 9.5 折 $6,384
  • 語言: 英文
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 9811639639
  • ISBN-13: 9789811639630
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

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商品描述

This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications.

The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed.

The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques.

The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.

商品描述(中文翻譯)

本書提供了對於週期性模式挖掘領域的介紹，回顧了最先進的技術，討論了最近的進展，並評估了開源軟體。週期性模式挖掘是資料挖掘領域中一個受歡迎且新興的研究領域。它涉及在時間資料庫中發現所有定期出現的模式。週期性模式挖掘的一個主要應用是分析客戶交易資料庫，以發現客戶定期購買的商品集合。發現這些模式對於理解客戶行為有多方面的影響。自從週期性模式挖掘的首個研究工作以來，已經發表了大量研究，並在這個領域取得了重大進展。本書由三個主要部分組成：介紹、演算法和應用。

第一章是對模式挖掘和週期性模式挖掘的介紹。討論了週期性、週期性支持、搜尋空間探索技術和剪枝策略的概念。還介紹了主要的演算法類型，如週期性頻繁模式增長、部分週期性模式增長和週期性高效用項集挖掘演算法。回顧了挑戰和研究機會。

接下來的章節介紹了在（1）交易資料庫、（2）時間資料庫、（3）定量時間資料庫和（4）大數據中發現週期性模式的最先進技術。然後，介紹了週期性模式的簡潔表示理論，以及使用隱私保護資料挖掘技術隱藏敏感資訊。

本書以幾個週期性模式挖掘的應用作結，包括在空氣污染數據分析、事故數據分析和交通擁堵分析中的應用。

作者簡介

Rage Uday Kiran is an associate professor at the University of Aizu in Japan. He has published over 50 articles in refereed journals and international conferences, such as EDBT, SSDBM, CIKM, IEEE FUZZY, PAKDD, DASFAA, DEXA and JSS. His current research interests include data mining, parallel computation, air pollution data analytics, traffic congestion data analytics, recommender systems, and ICTs for Agriculture.

Philippe Fournier-Viger is professor at the Harbin Institute of Technology. He has published more than 300 research papers with over 7200 citations. He is Associate Editor-in-Chief of Applied Intelligence and founder of the SPMF pattern mining library.

Jose Maria Luna is an assistant professor at the University of Cordoba, Spain. He received the Ph.D. degree in Computer Science from the University of Granada, Spain. He has published more than 30 papers in top ranked journals, most of them in the pattern mining field. He is author of two books, related to pattern mining, published by Springer: "Pattern Mining with Evolutionary Algorithms" and "Supervised Descriptive Pattern mining"

Jerry Chun-Wei Lin received his Ph.D. from the Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan in 2010. He is currently a full Professor with the Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. He has published more than 400 research articles in several top-tier conferences and journals. He has recognized as the most cited Chinese Researcher respectively in 2018, 2019, and 2020 by Scopus/Elsevier. He is the Fellow of IET (FIET), senior member for both IEEE and ACM.

Anirban Mondal an Associate Professor of Computer Science at Ashoka University, India. His research interests include database indexing, spatial databases, mobile data management, big data analytics and utility mining. He specializes in the domains of finance, retail and smart cities.

作者簡介(中文翻譯)

Rage Uday Kiran 是日本會津大學的副教授。他在經過審核的期刊和國際會議上發表了超過50篇文章，這些會議包括EDBT、SSDBM、CIKM、IEEE FUZZY、PAKDD、DASFAA、DEXA和JSS。他目前的研究興趣包括資料探勘、平行計算、空氣污染數據分析、交通擁堵數據分析、推薦系統以及農業的資訊與通信技術（ICTs）。

Philippe Fournier-Viger 是哈爾濱工業大學的教授。他發表了超過300篇研究論文，引用次數超過7200次。他是《應用智慧》（Applied Intelligence）的副主編，並且是SPMF模式挖掘庫的創始人。

Jose Maria Luna 是西班牙科爾多瓦大學的助理教授。他在西班牙格拉納達大學獲得計算機科學博士學位。他在頂尖期刊上發表了超過30篇論文，其中大多數與模式挖掘領域有關。他是兩本與模式挖掘相關的書籍的作者，這些書籍由Springer出版：《使用進化演算法的模式挖掘》（Pattern Mining with Evolutionary Algorithms）和《監督式描述性模式挖掘》（Supervised Descriptive Pattern mining）。

Jerry Chun-Wei Lin 於2010年在台灣國立成功大學計算機科學與資訊工程系獲得博士學位。他目前是挪威卑爾根西挪威應用科學大學計算機科學、電氣工程與數學科學系的正教授。他在多個頂尖會議和期刊上發表了超過400篇研究文章。他在2018、2019和2020年被Scopus/Elsevier認定為最被引用的華人研究者。他是IET的院士（FIET），同時也是IEEE和ACM的高級會員。

Anirban Mondal 是印度阿肖卡大學的計算機科學副教授。他的研究興趣包括資料庫索引、空間資料庫、行動數據管理、大數據分析和效用挖掘。他專注於金融、零售和智慧城市等領域。

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