DOSLP:Dataset of Student Location Prediction inside the University in India version2

When a student arrives on campus, especially in the morning or evening, it is crucial in the field of education to observe their Point of Interest Location (POIL). Thus, students would frequently visit various POILs on campus, such as the library and cafeteria. To gather the student POIL dataset from private technical universities in India, we devised and constructed a web interface for our study. The director of the computer science department at a university in India provided a letter of authorization. To make the dataset suitable for pattern analysis and student POIL prediction on university campuses, sensitive and identifiable student information has been removed. Moreover, we preprocess, analyze, and classify the number of students who spend time in the various university POILs by utilizing the student dataset. We also classify the gender distribution of the student population that spends time in the various campus POILs.当学生抵达校园，尤其早间或晚间时段时，观测其兴趣点位置（Point of Interest Location, POIL）在教育研究领域具备重要价值。学生通常会频繁到访校园内各类兴趣点，如图书馆、食堂等。为采集印度私立理工科院校的学生兴趣点数据集，本研究设计并搭建了专用网页界面。印度某高校计算机科学系系主任为本次研究出具了授权函。为使该数据集适配校园场景下的模式分析与学生兴趣点位置预测任务，所有敏感及可识别的学生个人信息均已被剔除。此外，本研究基于该学生数据集，对到访各类校园兴趣点的学生人数开展了预处理、分析与分类工作，同时还对到访各校园兴趣点的学生群体的性别分布进行了分类统计。