Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage

eBook Information

Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage ISBN  0471666556 Release Date  25 April 2007 Category  Data Mining Tags  mining,   0471666556,   "mining the web",   "data mining",   text mining,   "data mining the web",   mining the web,   content,   pattern,   pattern recognition,   data mining,   web + analytics,   data and mining,   structure,   data mining your website,   This book @Amazon  View Tools Google Search Web flazx.com

Description 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). Other books on Data Mining Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems) Fuzzy Modeling Tools for Data Mining and Knowledge Discovery (The Morgan Kaufmann Series in Data Management Systems) Advanced Data Mining Techniques Data Mining and Knowledge Discovery Technologies (Advances in Data Warehousing and Mining) Mobility, Data Mining and Privacy: Geographic Knowledge Discovery Survey of Text Mining II: Clustering, Classification, and Retrieval Emerging Technologies of Text Mining: Techniques and Applications Data Mining Patterns: New Methods and Applications Data Mining With Ontologies: Implementations, Findings and Frameworks (Premier Reference) Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage Principles of Data Mining (Undergraduate Topics in Computer Science) Intelligent Data Mining: Techniques and Applications (Studies in Computational Intelligence) Research And Trends in Data Mining Technologies And Applications (Advances in Data Warehousing and Mining Series) (Advances in Data Warehousing and Mining ... in Data Warehousing and Mining Series) Quality Measures in Data Mining (Studies in Computational Intelligence) Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)