RECOMMENDER BASED E-COMMERCE WEBSITE

Abstract : To overcome the product overload of online shoppers, a variety of recommendation methods have been developed. Recommender systems are being utilized by an ever increasing number of E-commerce sites to help consumers discover products to buy. The most of existing system gives the recommendation based on best selling product, on demographics of the consumer, or on an analysis of the past buying behavior of the consumer. Our purposed system based on the consumer reviews and advanced multi-criteria search engine. In this paper, we used a text mining approach to mine product features, opinions and their semantic similarity from Web opinion sources. The consumer can clearly see the strengths and Weaknesses of each product in the minds of existing consumer’s opinion. The system assists on-line shoppers or goal oriented shopper by suggesting the most effective navigation products for their specified criteria and preferences.

 EXISTING SYSTEM :

 ? The existing recommendation system lacks the capability of creating the difference on respective systems specifications meaning a review on specific attribute of system is utilized to measure the overall system or item’s rating. ? These kinds of feedbacks are accountable in existing systems while rating or comparing the complete product. ? The provided recommendations are user opinions based on products feature; the user can clearly understand the strengths and Weaknesses of each product in the minds of existing users.

 DISADVANTAGE :

 ? It is very challenging to recommend the products to new customers, therefore Demographics techniques are used to handle this kind of problem. ? To address this problem statement our recommendation system focuses on the product’s features, opinion and recommends & condemns it depending upon its feature, opinion and requirements of users fairly considering the reviews in the system. ? A new assessment mechanism is introduced to short out the new consumer problem of E- commerce recommendation.

 PROPOSED SYSTEM :

 • The proposed method involves forecasting an expected mistake that each system will generate for each user based on their historical behavior. • The proposed system depends on statistical analysis to solve the problem of a cold-start by providing a recommendation depending on the preferences matrix of the products. • The proposed system is a part of the commercial environment, which involves an e-commerce website, an e-bank system, and customers.

 ADVANTAGE :

 ? Goal-oriented shopping is efficient and purposeful, with a preplanned purchase in mind. ? We can rely on this product to make text analysis easier and more efficient for our research because it is a linguistics-based solution. ? The advantage of recommender system is their user-friendliness they don't need any extra search terms, they just use certain keyword according to user knowledge. This can be a significant advantage for inexperienced internet users.