DIFFERENCE BETWEEN DATA MINING AND WEB MINING
                     
DATA MINING AND WEB MINING



DIFFERENCE BETWEEN DATA 

MINING AND WEB MINING


What is Data Mining?

Data Mining(Knowledge Discovery in Databases)-The process of

discovering useful patterns or knowledge from different data

sources like databases, texts, images, audio and video and

web etc. The patterns must be valid, potentially useful, and

understandable. Data mining is a multi-disciplinary field

involving machine learning, statistics, databases, artificial

intelligence, information retrieval, and visualization.


What is Web Mining?

The application of data mining techniques to discover patterns from the

web and categorical extraction and evaluation with filtered information for

knowledge discovery from sophisticated web data and its appropriate web

services. It can be divided into three major categories-

1-Web Content Mining (WCM)aims to extract useful information or

knowledge from web data contents like text, image, audio, video records

etc.

2- Web Structure Mining (WSM) tries to discover useful knowledge from the

structure of hyperlinks and tags.

3-Web Usage Mining (WUM) refers to the discovery of user usage logs, http

logs, application server logs, etc.


DIFFERENCES


Comparison Web Mining Data Mining 

Definition Process used to extract 

information from web 

documents. 

Process used to extract 

hidden information from 

the database.

Scale It contains 10 million jobs 

in server database, and 

therefore search 

processing is not big. 

It contains 1 million jobs 

in database and search 

processing is large. 

Who does this?
Data scientists

Data engineers

Data scientists/Data 

analysts

Data engineers

Structure The information is 

obtained from structured, 

semi-structured and 

unstructured web forms. 

It gets the information 

from wide database. 

It obtains the information 

from explicit structure. It 

is not able to get all the 

information from wide 

database as compared to 

web mining. 


Comparison Web Mining Data Mining 

Concept

Pattern identification from 

data available in any 

systems.

Pattern identification from 

web data.

Process

Data extraction -> Pattern 

discovery -> Develop the 

feature/solve it 

(Algorithm)

Same process but on web 

using the web documents

Access Data is accessed publicly. 

In this, data is not hidden 

in web database and only 

permission is required to 

access the data from web 

log master. 

Data is accessed privately 

and only authorized user 

can access the data. 

Data It works upon on-line data. It works upon off-line data. 

Data Storage Data is stored in server 

logs and web server 

database. 

Data is stored in data 

warehouses. 


Comparison Web Mining Data Mining 

Techniques Web Content Mining, 

Graph Based Web Mining, 

Utilization in Web Mining, 

Text Mining and many 

others.

Artificial Neural Network, 

Decision Trees, Rule 

Induction, Nearest 

Neighbor Method and 

many others.

Challenges Complexity of web pages, 

web is too huge, relevancy 

of information, web is 

dynamic information 

source, diversity of user 

communicates etc.

Network settings, data 

quality, privacy 

preservation, scalability, 

complex and 

heterogeneous data, etc.

Tools
Machine learning 

algorithms

Scrappy,

PageRank,

Apache logs

How significant??

Many organizations are 

relying on data science 

results for decision 

making.

Web-related data pull 

would influence the 

existing data mining 

process.


APPLICATION AREAS


Data Mining 

Industry Application

Finance Credit Card Analysis

Insurance Claims, Fraud Analysis

Telecommunication Call record analysis

Transport Logistics management

Consumer goods promotion analysis

Data Service providers Value added data

Utilities Power usage analysis


Web Mining 

 The most dominant application area for WM is related to Internet based e-

commerce (business-to-consumer) and Web-based customer relationship

management (CRM) an integral part of E-business today.

 To discover knowledge for understanding the cause of any disease and its

treatment.

 The business benefits that Web mining affords to digital service providers

include personalization , collaborative filtering, enhanced customer

support, product and service strategy definition, particle marketing and

fraud detection.

 To track error done by hospital staff and enable them t correct the error

and prohibit them to repeat the same in future. To identify some patterns

to set the policies for health care centers and hospitals.


THANK YOU!!!