Exploiting Filtering approach with Web Scrapping for Smart Online Shopping : Penny Wise: A wise Tool for Online Shopping

With the advancement in technology and popularity of e-commerce, the number of online shopping websites have been increased rapidly in the cyber world. This made people's life easy because it is easy to shop through internet. But this also bring effort for people as they spend a lot of time and efforts to search best product deals and offers on e-commerce websites. They have to filter and compare data by themselves. It takes a lot of time and still there are chances of ambiguous results. This paper is based on web crawling and scraping methods applied for identifying best deals from five e-commerce websites. The framework is designed using HTML (Hypertext markup language) and CSS (Cascading style sheet) as front-end and PHP: Hypertext preprocessor language as back-end support. The scrapping scripts are written using python libraries and web crawling works on HTML labels. The novelty in this framework is that we are not storing scrapped data on local database. Instead the results are dynamically fetched and showed every time the user input the query. It will help to improvise the storage and processing ability. Furthermore, the data retrieval process accuracy is 93% with minimum computation and less time.