Skip to product information
1 of 1

Web Content Mining

Regular price £99.00
Sale price £99.00 Regular price £99.00
Sale Sold out
This book illustrates the concepts and applications of web mining from the nature of web data sources to discovering and representing the extracted knowledge. Starting with an overview of data mini...
Read More
  • Format:
  • 30 October 2025
View Product Details

This book illustrates the concepts and applications of web mining from the nature of web data sources to discovering and representing the extracted knowledge. Starting with an overview of data mining, it introduces web mining and draws comparisons between data mining and web mining. After this introduction the book covers data sources, categories and classes of web mining, including the subfields of Web Structure Mining, Web Usage Mining and Web Content Mining. it incorporates practical methods of analysing various web data sources and extracting knowledge by taking into consideration the unique challenges and multidisciplinary and novel approaches needed.

Key Features:

  • Focus on web mining applications in knowledge discovery in databases.
  • Includes techniques and applications.
  • Accompanying code and data sets
  • Reviews present state of play and future challenges
files/i.png Icon
Price: £99.00
Pages: 350
Publisher: Institute of Physics Publishing
Imprint: Institute of Physics Publishing
Publication Date: 30 October 2025
ISBN: 9780750348416
Format: eBook
BISACs:

COMPUTERS / Data Science / Data Analytics, Data mining, COMPUTERS / Data Science / General, Databases and the Web, Data capture and analysis

REVIEWS Icon

Introduction: Web Content Mining
The editors
Chapter 1: Unstructured Techniques
Dinh-Thuan Do , Ton Duc Thang University, Vietnam
Narayan C. Debnath, Eastern International University, Vietnam
Chapter 2: Structured Techniques
Nikhil Sharma, HMR Institute of Technology & Management, Delhi, India
Chapter 3: Semi-Structured Techniques
Nick Rahimi Southern Illinois University, Carbondale
Bidyut Gupta, Southern Illinois University, Carbondale
Chapter 4: Multimedia Data Techniques
K.Martin Sagayam, Department of ECE, Karunya Institute of Technology and Sciences,
Coimbatore, India
Chapter 5: Web Content Mining Techniques
Hubert Szczepaniuk, Warsaw University of Life Sciences, Poland
Ewa Stawicka, Warsaw University of Life Sciences, Poland
Chapter 6: Web Content Mining Algorithms
Reinaldo Padilha França, State University of Campinas (Unicamp), Brazil
Chapter 7: Web Content Mining Applications and Case Studies
Keith Sherringham, Sydney, Australia. Chapter 8: Exploring Hidden Content and Knowledge
Loai Tawalbeh, Texas A&M University, United States
Chapter 9: Evaluation Measures in Web Mining
AKM Bahalul Haque, North South University, Bangladesh
Bharat Bhushan, Sharda University, India
Ravinder Kumar, Shri Vishwakarma Skill University, India
Chapter 10: Practical Application in Content Mining
B. Gupta, Southern Illinios University, United states