Özet:

Recommendation systems are one kind of information filters, where the filters learn certain users interest based on their locations, past profiles with respect to finance, historical behaviour in social networking sites and then pre- dict their preferences for a given item. The advent of recommendation system has changed the way business is being done with users and it also strengthens the interaction between the user and the service providers. Therefore, building an effective system or tools for recommendation is the key to the success of any service. One such important service rendered towards the education system it the choices given to students for their career growth in higher education. This is done during the transition phase from schools to colleges, because, providing a good choice based on users ability like financial status, location, language and job prospects. On the other hand the preference choice should be the focus of collecting various data about the colleges that are satisfying the requirements of users and providing a good recommendation with colleges that have neces- sary infrastructure, placements, language, and fees structures. Thus, the con- text of both the users requirements and the recommendation outcome are take into account and evaluated through collaborative filtering technique. The pro- posed work collects various attributes from students using a survey form and then applies it to our context aware recommender system, which in turn calcu- lates similarity indexed between various combination of items and then pro- vides the most preferred choice of institution for the students to enroll upon for pursuing his higher education.

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