Survey Paper on Web Content Extraction & Classification

Over the last few years, web data extraction has gained popularity. Product information on the Ecommerce website floods the internet with big data. Web-based business sites these days have gotten one of the most significant hotspots for getting a large amount of relevant data. Wide range of software application designs to extract relevant data from web pages in order to draw in more business. The extracted data can be used for retailer business and data analysis purposes. The web pages on such sites are based on different technologies, and the generated web documents are in structured or unstructured formats. Manually extract such relevant product data and multimedia type Information from the websites is complex and time-consuming. After extraction of data needs to be classified because web content contains unwanted data e.g. design information, advertising content. This paper describes different Procedures for web document classification and extraction.

I. Introduction

The Internet has become an important source of data and concurrently a successful platform for business because internet has now become a large container of data that produces a deep source of data mining, from which extracting relevant data has one of the greatest challenges. web information is in the form of structured, unstructured, and semi-structured formats. Extracting relevant knowledge from these different formats has become a large field of research today. Web mining is part of data mining which can be describe as the process of using data mining procedures and algorithms to obtain valuable information from the internet, such as Web documents and services, hyperlinks, Web content, and server logs.