Here is a Presentation regarding web mining which is a blooming technology in the industry,here i have covered all the topics required for presentation. Hope u enjoy it.Please encourage to post more presentation documents.I can provide u the document also ,if anyone need comment below.

1. SEMINAR
ON
WEB MINING
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2. CONTENTS
Introduction
Definition of web mining
Data mining Vs Web mining
Taxonomy
Web content mining
Web structure mining
Web usage mining
Applications
Pros&Cons
Conclusion
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3. INTRODUCTION
 Nowadays, it has become necessary for users to
utilise automated tools to find, extract, filter &
evaluate desired information & resources.
 The target of search engines is only to discover
the resources on the web.
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4. WEB MINING
 Web mining refers to the overall process of
discovering potentially useful and previously
unknown information or knowledge from the
Web data.
 Web mining research – integrate research from
several research communities such as:
◦ Database (DB)
◦ Information retrieval (IR).
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5. DATA MINING WEB MINING
 Extraction of useful
patterns from data
sources are like
databases, texts, web,
images etc
 Extracting relevant
information hidden in
Web-related data,
like the hypertext
documents on web.
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6. Web Mining Taxonomy
Web Mining
Web Content
Mining
Web Usage
Mining
Web Structure
Mining
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7. 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)
 Database View
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8. WEB STRUCTURE MINING
Discovering structure information from web
Web graph : web pages as nodes & hyperlinks as
edges
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9. 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.
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10. WEB MINING ISSUES
 Size
◦ Grows at about 1 million pages a day
◦ Google indexes 9 billion documents
◦ Number of web sites
 Netcraft survey says 72 million sites
 Diverse types of data
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11. APPLICATIONS
 Personalized Services
 Improve website design
 System Improvement
 Predicting trends
 Carry out intelligent buisness
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12. ADVANTAGES
 High trade volumes
 Classify threats & fight against Terrorism
 Establish better customer relationship
 Increase profitability
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13. DISADVANTAGES
Invasion of Privacy
Discrimination by controversial attributes
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14. CONCLUSION
Rapidly growing area.Promising area of future
research.The proposed techniques aim at helping
Web users to learn an unfamiliar topic in-depth
and systematically.
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15. ANY
QUERIES??
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16. THANK YOU
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