A Novel Content Over Context Based Filtering for College Recommendation System and Enhanced Accuracy Rate Enabled Hybrid Framework

This research paper presents a novel algorithm for recommending colleges to students, which is based on both content and context filtering. The evaluation of the accuracy of content-based and context-based filtering algorithms was conducted on a sample size of N=10. The assessment of the sample size was conducted using GPower software, with a pre-test power of 0.8 and an alpha value of 0.05. The study has determined the mean accuracy of 83.96% for content-based filtering and 80.48% for context-based filtering. This paper also presents a comparison between the performance of content-based filtering and context-based filtering.