Web Interaction Mining Using Adaptive Feature Selection Basedpenta Layered Artificial Neural Network (AFS-Plan) Classifier

Predicting the objective of internet users contains different applications in the areas such as e-commerce,
entertainment in online, and several internet-based applications. The integral section of classifying the
internet queries based on accessible features such as contextual information, keywords and their semantic
relationships. This research article aims in proposing Adaptive Feature Selection based Penta Layered
Artificial Neural Network Classifier for web interaction mining. Around 31 participants are chosen and
given topics to search web contents. Parameters such as precision, recall and F1 score are taken for
comparing the proposed AFS-PLANN classifier with the ANN and PLANN. Results proved that the
proposed classifier attains better performance than that of the conventional ANN and PLANN.