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ABSTRACT
Decision making and understanding the behavior of the customer has become
vital and challenging problem for organizations to sustain their position in the
competitive markets. Technological innovations have paved breakthrough in faster
processing of queries and sub-second response time. Data mining tools have become
surest weapon for analyzing huge amount of data and breakthrough in making correct
decisions.
The objective of this paper is to analyze the huge amount of data thereby
exploiting the consumer behavior and make the correct decision leading to
competitive edge over rivals. Experimental analysis has been done employing
association rules using Market Basket Analysis to prove its worth over the
conventional methodologies.
SYSTEM ANALYSIS
EXISTING SYSTEM:
The Existing System is to making decision and understanding the behavior of the
customer has become vital and challenging problem for organizations to sustain their
position in the competitive markets.
Disadvantage:
1. The existing system did not use the combination of association rules and data
warehousing.
PROPOSED SYSTEM:
The proposed system is to analyze the huge amount of data thereby exploiting
the consumer behavior and make the correct decision leading to competitive edge
over rivals. Experimental analysis has been done employing association rules using
Market Basket Analysis to prove its worth over the conventional methodologies. The
proposed approach makes use of the traditional Apriori algorithm to generate a set of
association rules from a database.
Advantage:
1. To make the correct decision leading to competitive edge over rivals.
2. The proposed system to using the association rules with data warehousing.
MODULES:
 Admin login
 Query-similarity
 User-similarity
 Association rules
Admin login:
In This Module admin maintained various products of
Food and Electronic
Details with several databases. The databases have Food and Electronic cost, details,
and Performance of Food and Electronic details like various products, etc., and also
has Enhancement like Quality, Quantity, less cost etc.,
Query-similarity:
When customer login and search the Food and Electronic details with specific
price. Then Food and Electronic details to be appeared with the customer to desire/wish.
Details are displayed from different types of databases, using join query. Then, he gives
feedback to that product.
User - Similarity:
If he, expected more details for various product he go to search via usersimilarity. It shows more details. Then he takes decision and once again search he
wish. Then give another feedback to that product.
Association rules:
Association rule mining is a two step process: i) Find all frequent item set. By
definition each item set will occur at least as frequently as a pre-determined minimum
support count. ii) Generate strong association rules from the frequent item set: these
rules must satisfy minimum support and minimum confidence.
SYSTEM SPECIFICATION
Hardware Requirements:
•
System
: Pentium IV 2.4 GHz.
•
Hard Disk
: 40 GB.
•
Floppy Drive : 1.44 Mb.
•
Monitor
: 14’ Colour Monitor.
•
Mouse
: Optical Mouse.
•
Ram
: 512 Mb.
•
Keyboard
: 101 Keyboard.
Software Requirements:
•
Operating system
: Windows XP.
•
Coding Language
: ASP.Net with C#
• Data Base
: SQL Server 2005.