Online Consumer Satisfaction

Abstract— Customers satisfaction is the most important criteria before buying any product. Technology today has grown to such an extent that every smallest possible query is found on internet. An individual can express his reviews towards a product through Internet. This allows others to have a brief idea about the product before buying one for them. In this paper, we take into account all the challenges and limitations encountered while reading the online reviews and time being consumed in understanding quality of the product from the reviews. We include several methods and algorithms that help the consumer to understand the Quality of the product in better way.

Keywords— Aspect, Summarization, Categorization, Reviews, comments

I. INTRODUCTION

In early days we have to remove time from your busy schedule for shopping. We all know technology is increasing day by day. Due to advancement in technology shopping has become easy now as has step to our house itself in the form of online shopping. We simply sit at home and shop what we want and what we need.

In early days before buying any product we ask other people there opinion about the product, its quality and many more. Whereas now it become easy as the information is already available on the internet. The users are being given the opportunity to write their reviews about the product through internet. This has proved to be useful to other consumers as well.

Apart from the star rating system, reading reviews and getting a brief idea about the product is the preferred choice. One of the main drawbacks of this review system is that, ‘n’ number of users of a single product writes their views. So before buying any product it has become a habit for the users to refer the reviews at once and proceed with their selection. But reading the number of reviews and then coming to a conclusion is quite difficult. We come up with a solution by making a categorization method.

II. RELATED

Here we are trying to make it more convenient for the consumer to understand the quality of the product. All that the consumer has to do is open an e-commerce website, select the product of his own desire, then simple pass the comments on the website as input to the system. The system will pre-process the given comments according to the product. The product quality will be analyzed based on the aspects and the keywords that are obtained from the reviews. The aspects will be analyzed based on the reviews obtained and a short conclusion will be made. Here we will be using two main algorithms namely – Probabilistic Aspect Ranking Algorithm and Porter stemming Algorithm.

In Probabilistic Aspect Ranking Algorithm the aspects of the product are selected along with its related reviews from the comment. For example, for the comment say the “the touch is as smooth as butter”, here the aspect touch is related to smooth as butter, so when we apply the algorithm to this comment we get the relation as touch – smooth. So on we can the relation for each and every aspect mentioned in the