Using Data Mining Hospital Recommender System

Recommender systems help the users to get the useful information regarding their search. To overcome the disadvantages of content- based filtering and collaborative filtering, Hybrid filtering is one of the best suitable approaches. Hospital Recommendation Services have been gaining popularity these days. There are many applications and systems that are recommending hospitals based on the user’s requirements and to meet the patient satisfaction. These applications take the reviews of the patients and the users and based on these reviews, they recommend the hospitals. Also if a person is new to the location that he is currently residing, when the specialty is given as input by him, then these applications recommend the hospitals. But the problem is that everyone is not aware of the medical terms like specialties. For those people, “Health or hospital Service Recommendation System� comes handy. “Health Service Recommendation System� is an Android Application for finding hospitals within a specified range of distance and requirements provided by the client using the Naïve Bayes classification algorithm. Naïve Bayes algorithm classifies the specialty and thus helps in achieving the maximum accuracy compared to the other algorithms used. This application is helpful even for the people who are not aware of the specialties of the hospitals. This paper overcomes these issues by using Hybrid Filtering. This system fetches the information from the user and displays the nearby hospitals related to it. In this paper, the location of the user and the requirement of which type of hospital should be mentioned by the user itself. Among the detected hospitals it suggests the hospitals to users based on the user ratings. Based on the Hybrid filtering approach recommend the hospitals to the account holders. Depends on the specialty of the Hospital and user preference, the Similarity is calculated using the cosine similarity concept. In Hybrid filtering, we consider the constraint which was given by the user. The main objective of this paper is to recommend the best hospitals to the users which will be helpful in emergency situations methods.