Abstract
An effective fetching of the most relevant documents from the web is difficult due to the vast amount of information in all types of formats. The vast amount of data is very difficult to understand by machines, but humans can easily understand. The semantic web is a web of data that make capable machines to understands the data on web pages and also known as Web 3.0. Semantic Web is a way to increase the accuracy of information retrieval systems. Web mining is the application of data mining to extract knowledge from web data using data mining techniques, including web documents, hyperlinks between documents, usage logs of web sites etc. The semantic web mining is aimed at combining both the semantic web and web mining. The main aim is turning unstructured data into machine understandable data using semantic web tools so machine can respond to human queries in less time and avoid tedious work and automatically extract knowledge hidden in the vast amounts of web data using web mining tools. This paper focuses on the various Semantic-web approaches and challenges.
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