MULTIFACTOR SEMANTIC RANKING FOR EFFICIENT MUL TIPURPOSE PRODUCT LISTINGS

The product ranking models has been deployed to the various applications, where the larger volumes of the data entries is involved. The product ranking models includes the various factors for the ranking for the search list ranking, recommendation lists, etc. In this paper, the multifactor semantic ranking model has been incorporated for the purpose of search list ranking or recommendation raking list production. The proposed model utilizes the variety of the factors associated with the products, such as their popularity, total number of visitors to the product page, total purchases till date, trust factor of the product page, etc. These multiple factors are always distributed and defined in the multiple ranges, which must be normalized in order to make them compatible for the preparation of the colla borative index for the product ranking. In the proposed model, the accessibility, visitor number and page viability plays the important factors behind the efficiency of this model. The experimental results have shown the efficiency of the proposed model in the terms of time based analysis.