Web mining
- 1. Web Mining By : Renu Soni
- 2. Content ● Introduction to Web Mining ● Web Mining vs. Data Mining ● Types of Web Mining ● Web Usage Mining Model ● Challenges in Web Mining ● Pros of Web Mining ● Application of Web Mining
- 3. Introduction to Web Mining ● Extraction information from Web Documents & Services. ● Discover useful info from www. ● Useful to e-commerce site and e-services.
- 4. Web Mining vs. Data Mining Traditional Data Mining Web Data ● Data is structural & relational. ● Well-Defined tables,rows & constraints. ● Semi structured and unstructured. ● Readily available data. ● Rich in features & patterns.
- 5. Types of Web Mining 1. Web Content Mining ● Mining of data,information & knowledge from web data. ● Works according to content of input. ● For Example:-If an user wants to search for a particular book, then search engine provides the list of suggestions.
- 6. 2. Web Structure Mining ● Discover the link structure of hyperlink. ● Identify links of web pages. ● Produce the structural summary of website and similar web pages. ● Example: ○ It can be useful to companies to determine the connection between two commercial websites.
- 7. 3. Web Usage Mining ● Mining the Web-Log records. ● Find user access patterns of web pages. ● Server registers a web log entry for web pages. ● Techniques to discover web usage pattern are: ○ Session and visitor analysis ○ OLAP (Online Analytical Processing)
- 8. ● Web Usage Mining Model
- 9. ● Usage Mining Techniques ○ Data Preparation ■ Data Collection ■ Data Selection ■ Data cleaning ○ Data Mining ■ Navigation Patterns ■ Sequential Patterns
- 10. Challenges in Web Mining
- 11. Pros of Web Mining ● Enable Ecommerce to do personalized marketing,which eventually result in higher trade volumes. ● The government agencies are using this technology to classify threats and fight against terrorism. ● The predictive capability of the mining application can benefits the society by identifying criminal activities.
- 12. Application of Web Mining 02 Business Intelligence 03 Knowledge Management 04 Web Services 05 System Performance 01 Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis sit amet odio vel purus bibendum luctus. E-Commerce
- 13. Thank You.