MULTI - FACTOR REVIEW CLASSIFICATION ALGORITHM FOR PRODUCT PROFILE BUILDING USING PROBABILISTIC CLASSIFICATION

The online shopping portals have been grown their popularity over the recent years and have gained the multi - billion dollar business by selling the variety of the goods from their portals. The online shopping portals post the major problem to customers in the case of the pre - purchase verification of the goods, which is the major reason behind the problem arising with the higher number of after sales product returns. The touch and feel of the product during purchasing gives the customers metal satisfaction a s they completely investigate the product condition before paying the amount for purchasing. This factor is entirely missing from the online sales and the only factor available the customer review, which must be read entirely or the rating can be followed for the product quality. There are several cases come to fore for the false rating in the past, which also reduces the trust of the customer over such ratings. The customer review analysis algorithm with automatic reporting for the easy to access customer review factors can ease out the product quality evaluation process. In this paper, the proposed model entirely focuses upon the extraction and evaluation of the product quality based factor based upon the individual features, which gives the detailed revie w analysis and facilitates the users to easily decide upon their products. The proposed model has undergone the various kinds of the experiments and can be easily considered as the robust model. The proposed model has also outperformed the existing models in the terms of product review assessment and evaluation.