Performance Evaluation Based on Classification of Web Log Data: A Machine Learning Approach

The present study contributes to the understanding of artificial intelligence by assessing the importance of data in the generation of meaningful information and its prompt retrieval. Web mining is studied with the effective use of the WEKA tool. Web mining mainly deals with the extraction of knowledge flow and data present on the Web. Web mining can be categorized into three different categories Web structure mining, Web content mining, and Web usage mining. The present study emphasizes on Web usage mining that follows data processing under the three levels such as preprocessing, pattern discovery, and pattern analysis. The study findings reveal various algorithms can be adopted for data feeding and classification of data over some preprocessed method and comprised of the results. The findings of the study will be helpful for the users in acclimatizing with vivid algorithms that are associated with the Web data mining process which further gives them the sumptuous knowledge on how a dataset can be managed on Web usage according to their need of hours for generalizing the valid results.