Mining Sequential Patterns From Large Data Sets

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Mining Sequential Patterns From Large Data Sets

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Author : Wei Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-02-28

Mining Sequential Patterns From Large Data Sets written by Wei Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-28 with Computers categories.

In many applications, e.g., bioinformatics, web access traces, system u- lization logs, etc., the data is naturally in the form of sequences. It has been of great interests to analyze the sequential data to find their inherent char- teristics. The sequential pattern is one of the most widely studied models to capture such characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. In this book, we focus on sequential pattern mining. To meet different needs of various applications, several models of sequential patterns have been proposed. We do not only study the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. The objective of this book is to provide computer scientists and domain - perts such as life scientists with a set of tools in analyzing and understanding the nature of various sequences by : (1) identifying the specific model(s) of - quential patterns that are most suitable, and (2) providing an efficient algorithm for mining these patterns. Chapter 1 INTRODUCTION Data Mining is the process of extracting implicit knowledge and discovery of interesting characteristics and patterns that are not explicitly represented in the databases. The techniques can play an important role in understanding data and in capturing intrinsic relationships among data instances. Data mining has been an active research area in the past decade and has been proved to be very useful.

Frequent Pattern Mining

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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2014-08-29

Frequent Pattern Mining written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-29 with Computers categories.

This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.

Advances In Data And Web Management

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Author : Guozhu Dong
language : en
Publisher: Springer
Release Date : 2007-06-26

Advances In Data And Web Management written by Guozhu Dong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-26 with Computers categories.

This book constitutes the refereed proceedings of the joint 9th Asia-Pacific Web Conference, APWeb 2007, and the 8th International Conference on Web-Age Information Management, WAIM 2007, held in Huang Shan, China, June 2007. Coverage includes data mining and knowledge discovery, P2P systems, sensor networks, spatial and temporal databases, Web mining, XML and semi-structured data, privacy and security, as well as data mining and data streams.

Applications Of Security Mobile Analytic And Cloud Smac Technologies For Effective Information Processing And Management

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Author : Karthikeyan, P.
language : en
Publisher: IGI Global
Release Date : 2018-06-29

Applications Of Security Mobile Analytic And Cloud Smac Technologies For Effective Information Processing And Management written by Karthikeyan, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.

From cloud computing to big data to mobile technologies, there is a vast supply of information being mined and collected. With an abundant amount of information being accessed, stored, and saved, basic controls are needed to protect and prevent security incidents as well as ensure business continuity. Applications of Security, Mobile, Analytic, and Cloud (SMAC) Technologies for Effective Information Processing and Management is a vital resource that discusses various research findings and innovations in the areas of big data analytics, mobile communication and mobile applications, distributed systems, and information security. With a focus on big data, the internet of things (IoT), mobile technologies, cloud computing, and information security, this book proves a vital resource for computer engineers, IT specialists, software developers, researchers, and graduate-level students seeking current research on SMAC technologies and information security management systems.

Advanced Data Mining And Applications

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Author : Ronghuai Huang
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-28

Advanced Data Mining And Applications written by Ronghuai Huang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-28 with Computers categories.

This book constitutes the refereed proceedings of the 5th International Conference on Advanced Data Mining and Applications, ADMA 2009, held in Beijing, China, in August 2009. The 34 revised full papers and 47 revised short papers presented together with the abstract of 4 keynote lectures were carefully reviewed and selected from 322 submissions from 27 countries. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.

R Mining Spatial Text Web And Social Media Data

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Author : Bater Makhabel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-19

R Mining Spatial Text Web And Social Media Data written by Bater Makhabel and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-19 with Computers categories.

Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to real-world social media data using R Who This Book Is For This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path. What You Will Learn Discover how to manipulate data in R Get to know top classification algorithms written in R Explore solutions written in R based on R Hadoop projects Apply data management skills in handling large data sets Acquire knowledge about neural network concepts and their applications in data mining Create predictive models for classification, prediction, and recommendation Use various libraries on R CRAN for data mining Discover more about data potential, the pitfalls, and inferencial gotchas Gain an insight into the concepts of supervised and unsupervised learning Delve into exploratory data analysis Understand the minute details of sentiment analysis In Detail Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining. You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects. After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning Data Mining with R by Bater Makhabel R Data Mining Blueprints by Pradeepta Mishra Social Media Mining with R by Nathan Danneman and Richard Heimann Style and approach A complete package with which will take you from the basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.

Sequence Data Mining

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Author : Guozhu Dong
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-31

Sequence Data Mining written by Guozhu Dong and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-31 with Computers categories.

Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Current Topics In Artificial Intelligence

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Author : Pedro Meseguer
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-07

Current Topics In Artificial Intelligence written by Pedro Meseguer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-07 with Computers categories.

This book constitutes the refereed proceedings of the 13th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2009, held in Seville, Spain, in November 2009, in conjunction with the Workshop on Artificial Intelligence Technology Transfer, TTIA 2009. The 31 revised full papers presented were carefully selected from 125 submissions. The papers address the following topics: machine learning, multiagents, natural language, planning, diagnosis, evolutive algorithms and neural networks, knowledge representation and engineering, tutoring systems, uncertainty bayesian networks, vision, and applications.

Current Topics In Artificial Intelligence

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Author : Pedro Meseguer
language : en
Publisher: Springer
Release Date : 2010-07-05

Current Topics In Artificial Intelligence written by Pedro Meseguer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-05 with Computers categories.

This book constitutes the refereed proceedings of the 13th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2009, held in Seville, Spain, in November 2009, in conjunction with the Workshop on Artificial Intelligence Technology Transfer, TTIA 2009. The 31 revised full papers presented were carefully selected from 125 submissions. The papers address the following topics: machine learning, multiagents, natural language, planning, diagnosis, evolutive algorithms and neural networks, knowledge representation and engineering, tutoring systems, uncertainty bayesian networks, vision, and applications.

Data Mining And Big Data

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Author : Ying Tan
language : en
Publisher: Springer
Release Date : 2017-07-18

Data Mining And Big Data written by Ying Tan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-18 with Computers categories.

This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control.