PossibilityU’s data-driven approach to college matching isn’t new, but Mr. Jarratt’s recommendation algorithm is unique. Rather than starting with a list of questions about what students are looking for, PossibilityU asks users to enter up to three colleges that they are interested in. It then spits out a list of 10 other, similar colleges to consider. A premium paid subscription allows students to compare an unlimited number of colleges and provides application deadlines and other advice.
It’s kind of like Netflix’s movie suggestions, says Mr. Jarratt, who studies recommender systems like those used by the movie service and by Amazon.
This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well.