What is web mining?
Web mining is the process of extracting useful information from the World Wide Web. It involves techniques from data mining, machine learning, and artificial intelligence to identify patterns and trends from web data. Examples of web mining applications include spam filtering, link analysis, personalization, and text mining.
Web mining is the process of using data mining techniques to discover and extract information from web documents and services. It involves the analysis of various types of data available on the web, including web content, web structure, and web usage. Web mining can be categorized into three main types:

1. **Web Content Mining**: This focuses on extracting useful information from the content of web pages. It involves analyzing the text, images, and multimedia present on websites to derive meaningful patterns or insights. Techniques used in web content mining include natural language processing, information retrieval, and machine learning.

2. **Web Structure Mining**: This type examines the structure of the web itself, analyzing the links between different web pages. It aims to understand the relationships between various web entities and can help in identifying the importance of specific pages (e.g., PageRank). This analysis can also be useful for improving search engine algorithms and enhancing navigation.

3. **Web Usage Mining**: This involves analyzing user behavior on the web, typically by examining server logs or user activity data. It aims to understand how users interact with websites, which can help in improving website design, personalizing user experiences, and optimizing marketing strategies. Techniques used include clustering, classification, and pattern recognition.

Overall, web mining is a powerful tool for businesses and researchers to extract valuable insights from the vast amount of information available on the internet, enabling better decision-making and enhanced user experiences.