Paper Title : Customer Classification Of Discrete Customer Assets Data And Re-Ranking Of Classified Data
ISSN : 2394-2231
Year of Publication : 2020
MLA Style: Ms. N. Zahira Jahan, M.C.A., M. Phil ., Mr. T. Sasitharan, "Customer Classification Of Discrete Customer Assets Data And Re-Ranking Of Classified Data" Volume 7 - Issue 2 March - April,2020 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
APA Style: Ms. N. Zahira Jahan, M.C.A., M. Phil ., Mr. T. Sasitharan, "Customer Classification Of Discrete Customer Assets Data And Re-Ranking Of Classified Data" Volume 7 - Issue 2 March - April,2020 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org
The project “CUSTOMER CLASSIFICATION OF DISCRETE CUSTOMER ASSETS DATA AND RE-RANKING OF CLASSIFIED DATA”. Selecting useful information under the background of big data can help enterprises to classify customers more accurately. Outlier data includes important customer information. In order to study customer classification problem based on customer asset outlier data, a customer classification model based on outlier data analysis concerning customer asset is constructed successfully. The model is based on Variables in 4 dimensions including transaction frequency, types of products or services traded, transaction amount and client age. And using clustering before classification to divide twenty-five types of outlier customer data into four categories and corresponding marketing strategies also are put forward according to different classification of outlier customer data of a company. In addition, it also presents a flexible and effective re-ranking method, called CR-Re-ranking, to improve the retrieval effectiveness. To offer high accuracy on the top-ranked results, multi modal fusion re-ranking approach is used. Experimental results show that the quality, especially on the top-ranked results, is improved significantly.
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Data mining, customer clustering and I-Miner