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Web Data Mining

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Software Agents Based Web Data Mining: An Intelligent Approach
滿額折
出版日:2023/07/09 作者:Shakti Kundu  出版社:Lightning Source Inc  裝訂:平裝
優惠價: 1 1216
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出版日:2016/12/21 作者:G. Sreedhar (EDT)  出版社:Information Science Reference  裝訂:精裝
Explaining how to develop and evaluate decision support systems based on web data mining, computer scientists cover developing decision support systems, developing web mining systems, developing ef
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Web Data Mining ― Exploring Hyperlinks, Contents, and Usage Data
90 折
出版日:2013/08/03 作者:Bing Liu  出版社:Springer Verlag  裝訂:平裝
Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an
優惠價: 9 2807
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Web Data Mining
90 折
出版日:2011/07/01 作者:Bing Liu  出版社:Springer Verlag  裝訂:精裝
Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an
優惠價: 9 3375
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出版日:2017/11/25 作者:Matthew A. Russell; Mikhail Klassen  出版社:Oreilly & Associates Inc  裝訂:平裝
Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, GitHub, Instagram, and Google+? This new edition helps you discover who’s making connections with social media
優惠價: 1 1650
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New Horizons in Web Search, Web Data Mining, and Web-Based Applications
滿額折
出版日:2024/01/24 出版社:MDPI AG  裝訂:精裝
優惠價: 1 3062
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出版日:2017/02/28 作者:V. S. Kumbhar; K. S. Oza; R. S. Kamath  出版社:River Publishers  裝訂:精裝
Web mining is the application of data mining strategies to excerpt learning from web information, i.e. web content, web structure, and web usage data. With the emergence of the web as the predominant
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出版日:2016/08/12 作者:A. V. Senthil Kumar (EDT)  出版社:Information Science Reference  裝訂:精裝
Web usage mining is the application of data mining technologies to discover interesting usage patterns from web data in order to understand and better serve the needs of web-based applications. The bu
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出版日:2002/10/09 作者:Soumen Chakrabarti  出版社:Elsevier Science Ltd  裝訂:精裝
Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial s
優惠價: 1 3878
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出版日:2009/06/23 作者:M. Awad; Latifur Khan; Bhavani Thuraisingham; Lei Wang  出版社:Auerbach Pub UK  裝訂:精裝
Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction,
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出版日:2005/02/28 作者:Wei Wang (EDT); Jiong Yang (EDT)  出版社:Springer-Verlag New York Inc  裝訂:精裝
The focus of Mining Sequential Patterns from Large Data Sets is on sequential pattern mining. In many applications, such as bioinformatics, web access traces, system utilization logs, etc., the data i
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出版日:2010/07/30 作者:George Zheng; Athman Bouguettaya; Boualem Benatallah (FRW)  出版社:Springer-Verlag New York Inc  裝訂:精裝
Web Service Mining: For Biological Pathways presents the major issues and solutions to mining services on the Web. This book will focus specifically on a reference framework for web service mining, th
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出版日:2005/06/30 作者:Nikhil R. Pal (EDT); L. C. Jain (EDT)  出版社:Springer-Verlag New York Inc  裝訂:精裝
Presents the latest and most advanced tools and techniques available for data and web mining strategies with chapters written by leading world experts. Provides practicing engineers and scientists wit
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Mining of Massive Datasets
90 折
出版日:2020/02/29 作者:Jure Leskovec  出版社:Cambridge Univ Pr  裝訂:精裝
Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.
優惠價: 9 3509
無庫存
出版日:2017/06/07 作者:Jake Y. Chen; Stefano Lonardi  出版社:CRC Pr I Llc  裝訂:平裝
Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data min
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出版日:2015/03/15 作者:Hiroshi Ishikawa  出版社:Productivity Press  裝訂:精裝
This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analy
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出版日:2015/01/03 作者:Mick Benson  出版社:Ingram Pub Services  裝訂:精裝
This book consists of advanced information regarding data mining and their applications. It offers to aid data miners, researchers, scholars, and PhD students who aspire to practice data mining techni
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出版日:2013/06/18 作者:Jesus Mena  出版社:Taylor & Francis  裝訂:精裝
Data Mining Mobile Devices, also known as "Reality Mining," defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes poss
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出版日:2012/08/30 作者:Not Available (NA)  出版社:Taylor & Francis  裝訂:精裝
Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mini
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Practical Applications of Data Mining
滿額折
出版日:2010/12/14 作者:SUH SANG C.  出版社:JONES AND BARTLETT  裝訂:平裝
Practical Applications of Data Mining emphasizes both theory and applications of data mining algorithms. Various topics of data mining techniques are identified and described throughout, including clu
優惠價: 1 1100
無庫存
出版日:2010/12/06 作者:Yong Yin  出版社:Springer-Verlag New York Inc  裝訂:平裝
Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems.Data Mining is organis
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出版日:2010/06/18 作者:George Fernandez  出版社:CRC Press UK  裝訂:精裝
Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friendly data mining SAS tools. Integrating the statisti
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出版日:2009/09/01 作者:Jake Y. Chen (EDT); Stefano Lonardi (EDT)  出版社:Chapman & Hall  裝訂:精裝
Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data min
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This book contains valuable studies in data mining from both foundational and practical perspectives. The foundational studies of data mining may help to lay a solid foundation for data mining as a sc
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出版日:2004/08/02 作者:Anthony Scime (EDT)  出版社:Igi Global  裝訂:精裝
Web Mining is moving the World Wide Web toward a more useful environment in which users can quickly and easily find the information they need. Web Mining uses document content, hyperlink structure, an
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Introduction to Data Mining (GE)
95 折
出版日:2019/07/15 作者:Pang-Ning Tan ; Michael Steinbach ; Anuj Karpatne ; Vipin Kumar  出版社:PEARSON  裝訂:平裝
Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. Th
優惠價: 95 1349
無庫存
出版日:2019/02/28 作者:Parteek Bhatia  出版社:Cambridge Univ Pr  裝訂:平裝
Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are
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出版日:2018/11/13 作者:Yuan Yao; Xing Su; Hanghang Tong  出版社:Springer-Nature New York Inc  裝訂:平裝
This SpringerBrief presents a typical life-cycle of mobile data mining applications, including:data capturing and processing which determines what data to collect, how to collect these data,
優惠價: 1 3499
無庫存
出版日:2018/02/28 作者:Robert Stahlbock (EDT); Mahmoud Abou-nasr (EDT); Gary M. Weiss (EDT)  出版社:Stylus Pub Llc  裝訂:平裝
This volume contains the proceedings of the 2017 International Conference on Data Mining (DMIN'17).
優惠價: 1 3998
無庫存
出版日:2017/06/07 作者:Yukio Ohsawa (EDT); Katsutoshi Yada (EDT)  出版社:Chapman & Hall  裝訂:平裝
Data Mining for Design and Marketing shows how to design and integrate data mining tools into human thinking processes in order to make better business decisions, especially in designing and marketing
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出版日:2016/11/24 作者:Yun Yang  出版社:Elsevier Science Ltd  裝訂:平裝
Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning, and the fundamental problems of tem
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出版日:2016/09/16 作者:Elatia  出版社:John Wiley & Sons Inc  裝訂:精裝
Data mining is an increasingly valuable tool within the institution of higher education. Educational Data Mining (EDM) has emerged as a field in its own right, focusing on data mining techniques
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出版日:2016/04/27 作者:Oliviero Carugo (EDT); Frank Eisenhaber (EDT)  出版社:Humana Pr Inc  裝訂:精裝
This volume details several important databases and data mining tools. Data Mining Techniques for the Life Sciences, Second Editionguides readers through archives of macromolecular three-dimensional s
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出版日:2015/07/15 作者:He Zengyou  出版社:Elsevier Science Ltd  裝訂:精裝
Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving real bioinformatics problems, including problem definition, data
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出版日:2015/06/24 作者:Piegorsch  出版社:John Wiley & Sons Inc  裝訂:平裝
A comprehensive introduction to statistical methods for data mining and knowledge discovery.Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven so
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出版日:2015/04/27 作者:Charu C. Aggarwal  出版社:Springer-Verlag New York Inc  裝訂:精裝
This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issu
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出版日:2014/12/14 作者:Carlos Fern憳ez Llatas (EDT); Juan Miguel Garc??g?z (EDT)  出版社:Springer Verlag  裝訂:精裝
This volume complies a set of Data Mining techniques and new applications in real biomedical scenarios. Chapters focus on innovative data mining techniques, biomedical datasets and streams analysis, a
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出版日:2014/09/11 作者:Garc?? Salvador; Juli憳? Herrera Luengo Francisco  出版社:Springer Verlag  裝訂:精裝
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsis
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出版日:2014/03/07 作者:Yongchuan Tang  出版社:Springer-Verlag New York Inc  裝訂:精裝
Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy.Uncertainty Modeling for Data Mining: A Label Se
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出版日:2013/08/07 作者:Nong Ye  出版社:Taylor & Francis  裝訂:精裝
Written for those with a science and engineering background, this book introduces and explains a comprehensive set of data mining techniques from various data mining fields. Concepts and methodologies
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