Web Data Mining

The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book.

Web Data Mining

Author: Bing Liu

Publisher: Springer Science & Business Media

ISBN: 9783642194603

Page: 624

View: 576

Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.

Data Mining the Web

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, ...

Data Mining the Web

Author: Zdravko Markov

Publisher: John Wiley & Sons

ISBN: 0471666556

Page: 218

View: 228

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification, clustering, language processing), structure (graphs, hubs, metrics), and usage (modeling, sequence analysis, performance).

Mining the Web

The definitive book on mining the Web from the preeminent authority.

Mining the Web

Author: Soumen Chakrabarti

Publisher: Morgan Kaufmann

ISBN: 9781558607545

Page: 345

View: 720

The definitive book on mining the Web from the preeminent authority.

Mining the Web

Coauthored by two bestselling data mining authors, Mining the Web explains, for corporate decision makers, IT managers, and database marketers, how data mining principles and techniques can be applied to various types of Web sites.

Mining the Web

Author: Gordon S. Linoff

Publisher: John Wiley & Sons

ISBN:

Page: 348

View: 577

Introduces business and technical managers to the exciting new frontier in database technology Web sites gather a lot of detailed information about customers. Unfortunately, most companies lack the means to use that information to improve their marketing and customer support functions. Considered by most experts to be the new frontier in the database and data warehousing fields, Web mining solves that problem. Coauthored by two bestselling data mining authors, Mining the Web explains, for corporate decision makers, IT managers, and database marketers, how data mining principles and techniques can be applied to various types of Web sites. More importantly, they describe techniques for using the resulting goldmine of business data to develop more effective advertising campaigns and better customer service.

Data Mining VIII

Technology plays an active role in the relationship of Data Mining to environmental conservation planning.Bringing together papers presented at the Eighth International Conference on Data, Text and Web Mining and their Business Applications ...

Data Mining VIII

Author: A. Zanasi

Publisher: WIT Press

ISBN: 1845640810

Page: 346

View: 141

Information Engineering Management has found applications in many areas, including environmental conservation, economic planning, resource integration, cartography, urban planning, risk assessment, pollution control and transport management systems. Technology plays an active role in the relationship of Data Mining to environmental conservation planning.Bringing together papers presented at the Eighth International Conference on Data, Text and Web Mining and their Business Applications, this book addresses the new developments in this important field. Featured topics include: Text Mining; Web Content, Structures and Usage Mining; Clustering Technologies; Categorisation Methods; Link Analysis; Data Preparation; Applications in Business, Industry and Government; Applications in Science Engineering; National Security; Customer Relationship Management; Competitive Intelligence; Mining Environment and Geospatial Data; Business Process Management (BPM); Enterprise Information Systems; Applications of GIS and GPS; Applications of MIS; Remote Sensing; Information Systems Strategies and Methodologies and Bio Informatics.

Dark Web

This work aims to provide an interdisciplinary and understandable monograph about Dark Web research along three dimensions: methodological issues in Dark Web research; database and computational techniques to support information collection ...

Dark Web

Author: Hsinchun Chen

Publisher: Springer Science & Business Media

ISBN: 146141556X

Page: 454

View: 321

The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach. We aim to collect "ALL" web content generated by international terrorist groups, including web sites, forums, chat rooms, blogs, social networking sites, videos, virtual world, etc. We have developed various multilingual data mining, text mining, and web mining techniques to perform link analysis, content analysis, web metrics (technical sophistication) analysis, sentiment analysis, authorship analysis, and video analysis in our research. The approaches and methods developed in this project contribute to advancing the field of Intelligence and Security Informatics (ISI). Such advances will help related stakeholders to perform terrorism research and facilitate international security and peace. This monograph aims to provide an overview of the Dark Web landscape, suggest a systematic, computational approach to understanding the problems, and illustrate with selected techniques, methods, and case studies developed by the University of Arizona AI Lab Dark Web team members. This work aims to provide an interdisciplinary and understandable monograph about Dark Web research along three dimensions: methodological issues in Dark Web research; database and computational techniques to support information collection and data mining; and legal, social, privacy, and data confidentiality challenges and approaches. It will bring useful knowledge to scientists, security professionals, counterterrorism experts, and policy makers. The monograph can also serve as a reference material or textbook in graduate level courses related to information security, information policy, information assurance, information systems, terrorism, and public policy.

Mining the Social Web

With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re ...

Mining the Social Web

Author: Matthew A. Russell

Publisher: O'Reilly Media

ISBN: 1491973528

Page: 432

View: 481

Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter. Get a straightforward synopsis of the social web landscape Use Docker to easily run each chapter’s example code, packaged as a Jupyter notebook Adapt and contribute to the code’s open source GitHub repository Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect Apply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognition Build beautiful data visualizations with Python and JavaScript toolkits

Web Data Mining and the Development of Knowledge Based Decision Support Systems

Featuring extensive coverage across a range of relevant perspectives and topics, such as semantic web, machine learning, and expert systems, this book is ideally designed for web developers, internet users, online application developers, ...

Web Data Mining and the Development of Knowledge Based Decision Support Systems

Author: Sreedhar, G.

Publisher: IGI Global

ISBN: 1522518789

Page: 409

View: 664

Websites are a central part of today’s business world; however, with the vast amount of information that constantly changes and the frequency of required updates, this can come at a high cost to modern businesses. Web Data Mining and the Development of Knowledge-Based Decision Support Systems is a key reference source on decision support systems in view of end user accessibility and identifies methods for extraction and analysis of useful information from web documents. Featuring extensive coverage across a range of relevant perspectives and topics, such as semantic web, machine learning, and expert systems, this book is ideally designed for web developers, internet users, online application developers, researchers, and faculty.

Data Mining Techniques

This Book Addresses All The Major And Latest Techniques Of Data Mining And Data Warehousing.

Data Mining Techniques

Author: Arun K. Pujari

Publisher: Universities Press

ISBN: 9788173713804

Page: 288

View: 128

This Book Addresses All The Major And Latest Techniques Of Data Mining And Data Warehousing. It Deals With The Latest Algorithms For Discussing Association Rules, Decision Trees, Clustering, Neural Networks And Genetic Algorithms. The Book Also Discusses The Mining Of Web Data, Temporal And Text Data. It Can Serve As A Textbook For Students Of Compuer Science, Mathematical Science And Management Science, And Also Be An Excellent Handbook For Researchers In The Area Of Data Mining And Warehousing.

Data Mining Techniques

Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.

Data Mining Techniques

Author: Michael J. A. Berry

Publisher: John Wiley & Sons

ISBN: 0471470643

Page: 643

View: 878

Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.

Machine Interpretation of Patterns

This review volume provides from both theoretical and application points of views, recent developments and state-of-the-art reviews in various areas of pattern recognition, image processing, machine learning, soft computing, data mining and ...

Machine Interpretation of Patterns

Author:

Publisher:

ISBN: 9814465445

Page:

View: 960

Data Mining and Predictive Analytics

Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, ...

Data Mining and Predictive Analytics

Author: Daniel T. Larose

Publisher: John Wiley & Sons

ISBN: 1118116194

Page: 824

View: 360

Learn methods of data analysis and their application to real-world data sets. Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content

WEBKDD 2002 Mining Web Data for Discovering Usage Patterns and Profiles

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Mining Web Data, WEBKDD 2002, held in Edmonton, Canada, in July 2002.

WEBKDD 2002   Mining Web Data for Discovering Usage Patterns and Profiles

Author: Osmar Za?ane

Publisher: Springer Science & Business Media

ISBN: 3540203044

Page: 179

View: 252

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Mining Web Data, WEBKDD 2002, held in Edmonton, Canada, in July 2002. The 10 revised full papers presented together with a detailed preface went through two rounds of reviewing and improvement and were selected from 23 submissions. The papers are organized in topical sections on categorization of users and usage, prediction and recommendation, and evaluation of algorithms.

Web Data Mining and Applications in Business Intelligence and Counter Terrorism

The explosion of Web-based data has created a demand among executives and technologists for methods to identify, gather, analyze, and utilize data that may be of value to corporations and organizations.

Web Data Mining and Applications in Business Intelligence and Counter Terrorism

Author: Bhavani Thuraisingham

Publisher: CRC Press

ISBN: 9780203499511

Page: 544

View: 867

The explosion of Web-based data has created a demand among executives and technologists for methods to identify, gather, analyze, and utilize data that may be of value to corporations and organizations. The emergence of data mining, and the larger field of Web mining, has businesses lost within a confusing maze of mechanisms and strategies for obta

WEBKDD 2001 Mining Web Log Data Across All Customers Touch Points

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Mining Web Data, WEBKDD 2001 held in San Francisco, CA, USA in August 2001.

WEBKDD 2001   Mining Web Log Data Across All Customers Touch Points

Author: Ron Kohavi

Publisher: Springer Science & Business Media

ISBN: 3540439692

Page: 166

View: 612

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Mining Web Data, WEBKDD 2001 held in San Francisco, CA, USA in August 2001. The seven revised full papers went through two rounds of reviewing an improvement. The book addresses key issues in mining Web log data for e-commerce. The papers are devoted to predicting user access, recommender systems and access modeling, and acquiring and modeling data and patterns.

Data Mining Southeast Asia Edition

Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, ...

Data Mining  Southeast Asia Edition

Author: Jiawei Han

Publisher: Elsevier

ISBN: 9780080475585

Page: 800

View: 154

Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data. A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects Complete classroom support for instructors at www.mkp.com/datamining2e companion site

Web Mining and Social Networking

This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems ...

Web Mining and Social Networking

Author: Guandong Xu

Publisher: Springer Science & Business Media

ISBN: 9781441977359

Page: 210

View: 250

This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.

Data Analysis and Data Mining

This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data.

Data Analysis and Data Mining

Author: Adelchi Azzalini

Publisher: Oxford University Press

ISBN: 0199942714

Page: 288

View: 865

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data. Aided by a diverse range of statistical methods and techniques, readers will move from simple problems to complex problems. Through these case studies, authors Adelchi Azzalini and Bruno Scarpa explain exactly how statistical methods work; rather than relying on the "push the button" philosophy, they demonstrate how to use statistical tools to find the best solution to any given problem. Case studies feature current topics highly relevant to data mining, such web page traffic; the segmentation of customers; selection of customers for direct mail commercial campaigns; fraud detection; and measurements of customer satisfaction. Appropriate for both advanced undergraduate and graduate students, this much-needed book will fill a gap between higher level books, which emphasize technical explanations, and lower level books, which assume no prior knowledge and do not explain the methodology behind the statistical operations.

Collaborative Filtering Using Data Mining and Analysis

Featuring emergent research and optimization techniques in the areas of opinion mining, text mining, and sentiment analysis, as well as their various applications, this book is an essential reference source for researchers and engineers ...

Collaborative Filtering Using Data Mining and Analysis

Author: Bhatnagar, Vishal

Publisher: IGI Global

ISBN: 1522504907

Page: 309

View: 580

Internet usage has become a normal and essential aspect of everyday life. Due to the immense amount of information available on the web, it has become obligatory to find ways to sift through and categorize the overload of data while removing redundant material. Collaborative Filtering Using Data Mining and Analysis evaluates the latest patterns and trending topics in the utilization of data mining tools and filtering practices. Featuring emergent research and optimization techniques in the areas of opinion mining, text mining, and sentiment analysis, as well as their various applications, this book is an essential reference source for researchers and engineers interested in collaborative filtering.

Principles of Data Mining

This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas.

Principles of Data Mining

Author: Max Bramer

Publisher: Springer

ISBN: 1447173074

Page: 526

View: 337

This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. This expanded third edition includes detailed descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift.