14-05-2012, 04:42 PM
Weighted Association Rule Mining Clustering and in non-binary search space
101.Weighted Association Rule Mining Clustering and in non.docx (Size: 17.28 KB / Downloads: 30)
ABSTRACT
Association rule mining is a key issue in data mining.
However, the classical models ignore the difference between the transactions, and the weighted association rule mining does not work on databases with only binary attributes.
In this paper, we introduce a new measure w-support, which does not require pre-assigned weights.
It takes the quality of transactions into consideration using link-based models.
A fast mining algorithm is given, and a large amount of experimental results are presented.
The weights are completely derived from the internal structure of the database based on the
Assumption that good transactions consist of good items.
EXISTING SYSTEM:
In this system normally users can zxrate the products in the website .here the top ten products are getting by using pre assigned weights, so apart from top ten products we can display the top one product according to the support system.
Demerits of existing system:
There is no calculation of quality transaction.
There no estimation of awareness of user.
Chance of getting quality product is very less.
PROPOSED SYSTEM:
In this system once a registered user rate a product, analysis is made on the database and the role of the user in the rating system is identified and rate value of the product is concluded depending upon the his role, rate value is taken from the threshold value which we get from analysis conclusion, while the top product is to be calculated a scan is made on the database top ten user are identified then the top product rated by them is found and saved to location, this process is carried out for each and everyone in the top ten user list, finally a analysis is made over top product rated by the top ten user and we get to conclusion which is the best product, by this we get perfect result from this analysis.
Merits of proposed system:
It provides quality of transactions for the particular user.
It provides w-support value based on the transactions.
By using this system easily we can study the awareness of the different users.
Modules:
1. Preprocessing.
2. Support Based Rating.
3. W-Support Based Rating.
4. Support vs W-Support.
Preprocessing:
Our Preprocessing Module has following Sub-Modules:
1. User Registration
In this Module website visitor register themselves in this website, as registered users can only rate the products.
2. Product Registration
In this Module product viewed in this website are registered, only administrator has the privilege to register the products.