The semantic web is an extension of the current web that provides a standardstructure for data representation and reasoning, allowing content to be readable for both humans and machines in a form known as ontological knowledgebases. The goal of the Semantic Web is to be used in large-scale technologies or systems such as search engines, healthcare systems, and social mediaplatforms. Some challenges may deter further progress in the development ofthe Semantic Web and the associated web mining processes. In this reviewpaper, an overview of Semantic Web mining will examine and analyze challenges with data integration, dynamic knowledge-based methods, efficiencies,and data mining algorithms regarding ontological approaches. Then, a reviewof recent solutions to these challenges such as clustering, classification, association rule mining, and ontological building aides that overcome the challengeswill be discussed and analyzed.