COMPARATIVE ANALYSIS TO CONQUER SEMANTIC INTERPRETABILITY IN SEMANTIC WEB MINING

In the past few years, a lot of consideration has been dedicated to improving web search and recommender systems through data mining. It makes search through large quantities of data for useful information. Thus it is difficult to fetch the effective and meaningful and relevant data from such a large amount of data because the machines are not capable to understand the data in the way a human understands. The semantic web mining is discovered to make the machines capable to understand such a large amount of data on web pages. The semantic web mining is the combination of two fields i.e. semantic web and web mining. The semantic web mining utilizes the semantics to improve the mining process and utilizes the mining process to create the semantics. Semantic web mining go through the insights related to the meaning of web resources and searched queries so that the more relevant information can be extracted. This study provides a review to the web mining, categories of web mining, correlation of web mining and semantic mining, techniques of semantic web mining and few of the past work of this field. The interest of this study is to have a knowledge regarding the previous work that has been done to enhance the performance of semantic web mining.