A hybrid web analytic approach through click enabled vision based page segmentation in quest software for school students

Abstract

The primary goal of this study is to optimize web content for a positive user experience and to develop a data-driven methodology to assess the success of visitor flow on a website for school children. Through Vision-Based Page Segmentation, the suggested study work intends to broaden the stated web approach’s reach and statistical inference. The improvisation has been made accordingly with the semantic structure observed from each node with the designated degree of coherence to indicate the content in spatial and block based on visual perception for each event. The click count (number of clicks) is calculated for all the possibilities of Quest Software. The most frequently accessed event is displayed at the top to enhance usability and visibility with an accuracy of about 92.80%. From the experimental analysis, it has been observed that most of the students preferred events corresponding to drawing, rhymes, and rangoli with a willingness rate of above 80%, respectively. Statistical analysis has been made using chi-square analysis, and it has been found that the levels from A to D are significant for three years with a P-value < 0.001. Sentimental analysis of feedback collected from the participants about the events is also done, and the most preferred event is suggested for the upcoming years.