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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning;

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Web Data Mining

This book provides a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered;

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Advances in Data and Web Management

Conference on Web-Age Information Management, WAIM 2007, held in Huang Shan, China, June 2007. Coverage includes data mining and knowledge discovery;

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Mining User Navigation Patterns from Web Access Log Files

of people. Web Mining aims to discover the informative knowledge or information from massive data sources available on the Web by using data mining;

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Web Data Mining and Applications in Business Intelligence and Counter-Terrorism

utilize data that may be of value to corporations and organizations. The emergence of data mining, and the larger field of Web mining, has;

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Data Mining The Web

This book introduces the reader to methods of data mining on the web, including uncovering patterns in web content (classification;

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Web Information Systems Engineering WISE 2018

, social network, microblog data analysis, graph data, information extraction, text mining, recommender systems, medical data analysis, Web;

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Advanced Data Mining and Applications

algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics;

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Mining the Web

Mining the Web: Discovering Knowledge from Hypertext Data is the first book devoted entirely to techniques for producing knowledge from the;

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Web Content Mining from Hidden Web

complete data. The hidden Web, also known as the invisible Web or deep Web, has given rise to a new issue of Web mining research. Most documents;

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Extracting Knowledge From Opinion Mining

Data mining techniques are commonly used to extract meaningful information from the web, such as data from web documents, website usage;

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Web Information Systems Engineering - WISE 2017

selected from 195 submissions. The papers cover a wide range of topics such as microblog data analysis, social network data analysis, data mining;

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Web Information Systems Engineering - WISE 2017

selected from 195 submissions. The papers cover a wide range of topics such as microblog data analysis, social network data analysis, data mining;

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Machine Learning and Data Mining in Pattern Recognition

specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining.;

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Machine Learning and Data Mining in Pattern Recognition

classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image;

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Machine Learning and Data Mining in Pattern Recognition

data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.;

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Machine Learning and Data Mining in Pattern Recognition

mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.;

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Machine Learning and Data Mining in Pattern Recognition

for the different multimedia data types such as image mining, text mining, video mining and Web mining.;

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Social Big Data Mining

data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language;

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Social Big Data Mining

data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language;

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Advanced Data Mining and Applications

mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification;

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Data Security, Data Mining & Data Management

In this book, the authors discuss the new technologies and challenges of data security, data mining and data management. Topics include;

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Data Mining

Perspectives Classification, Clustering, Association Web, Text, Multimedia Mining Late Breaking Papers and Position Papers: Data Mining;

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Web Mining

Web mining is the application of data mining strategies to excerpt learning from web information, i.e. web content, web structure, and web;

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Data Mining

Thorough in its coverage from basic to advanced topics, this book presents the key algorithms and techniques used in data mining. An;

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Machine Learning and Data Mining in Pattern Recognition

and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two;

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Mining of Massive Datasets

The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining;

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