1. Web Mining Department of Computer Science and Engg.
Lovely professional university
February 18, 2019
Web Mining

2. INTRODUCTION With the explosive growth of information sources available on world wide web, it has become increasingly necessary for users to utilize automated tools in finding the desired information resources, these factors give rise to the necessity of creating server side & client side intelligent system that can effectively mine for knowledge.
February 18, 2019
Web Mining

3. Web Mining
Web mining - data mining techniques to automatically discover and extract information from Web documents/services.
Web mining research – integrate research from several research communities such as:
Database (DB)
Information retrieval (IR)
February 18, 2019
Web Mining

4. Mining the World-Wide Web
WWW is huge, widely distributed, global information source for
Information services: news, advertisements, consumer information, financial management, education, government, e-commerce, etc.
Hyper-link information
Access and usage information
Web Site contents and Organization
February 18, 2019
Web Mining

5. Mining the World-Wide Web
Growing and changing very rapidly
Broad diversity of user communities
Only a small portion of the information on the Web is truly relevant or useful to Web users
How to find high-quality Web pages on a specified topic?
WWW provides rich sources for data mining
February 18, 2019
Web Mining

6. Challenges on WWW Interactions
Finding Relevant Information
Creating knowledge from Information available
Personalization of the information
Learning about customers / individual users
Web Mining can play an important Role!
February 18, 2019
Web Mining

7. Web Mining: more challenging
Problems
The “abundance” problem
Limited coverage of the Web
Limited query interface based on keyword-oriented search
Dynamic and semistructured
February 18, 2019
Web Mining

8. Web Mining : Subtasks Resource Finding
Task of retrieving intended web-documents
Information Selection Automatic selection and pre-processing specific information from retrieved web resources
Generalization
Automatic Discovery of patterns in web sites
Analysis
Validation and / or interpretation of mined patterns
February 18, 2019
Web Mining

9. Web Mining Taxonomy Web Mining Web Content Mining Web Structure Mining
Web Usage Mining
February 18, 2019
Web Mining

10. Web Content Mining
Discovery of useful information from web contents / data / documents
Web data contents: text, image, audio, video,
Information Retrieval View ( Structured + Semi-Structured)
Assist / Improve information finding
Filtering Information to users on user profiles
Database View
Model Data on the web
Integrate them for more sophisticated queries
February 18, 2019
Web Mining

11. Web Structure Mining
To discover the link structure of the hyperlinks at the inter-document level to generate structural summary about the Website and Web page.
Direction 1: based on the hyperlinks, categorizing the Web pages and generated information.
Direction 2: discovering the structure of Web document itself.
Direction 3: discovering the nature of the hierarchy or network of hyperlinks in the Website of a particular domain.
February 18, 2019
Web Mining

12. Web Usage Mining Web usage mining also known as Web log mining
mining techniques to discover interesting usage patterns from the secondary data derived from the interactions of the users while surfing the web
February 18, 2019
Web Mining

13. Web Usage Mining Applications
Target potential customers for electronic commerce
Enhance the quality and delivery of Internet information services to the end user
Improve Web server system performance
Identify potential prime advertisement locations
Improve site design
Fraud/intrusion detection
Predict user’s actions (allows prefetching)
February 18, 2019
Web Mining

14. CONCLUSION : The proposed techniques aim at helping Web users to learn an unfamiliar topic in-depth and systematically This is an efficient system to discover and organize knowledge on the web, in a way similar to a traditional book, to assist learning.
February 18, 2019
Web Mining

15. THANK YOU
By:
Choshu jindal
A1807A17
February 18, 2019
Web Mining