• B.Rani
• R.Venkateshwarlu
• Dr. R. Jegadeesan
• V.Sindhu
• Dr.S.Prabaharan

Data mining is a procedure to discover designs at costly informational indices that include the intersection strategy of AI measurements and the database framework. The location recommendation helps people find attractive places with social and geographic information, but addresses the problem of cold start that can appear if we do not have enough information about the element. This is the situation that mostly occurs among new registered users. Due to human mobility, data is shared on social networks. One method is to incorporate them into explicit comments that are widely used in the research field of the recommendation system. They are often informed of the numerical rating of users to express their preferences. A content-aware collaborative filter framework based on implicit feedback in which information is easier to collect. The implicit feedback system performs passive tracking of different types of user behavior, such as purchase history, observation trends and persuasive movement to show user preferences. Do not does not have any immediate contribution from users with respect to preferences. And an efficient optimization algorithm used to scale linearly with the size of the data and the size of the characteristics and develop their relationship with the grafication of the Laplacian grid matrix of regularization. Finally, the data set of social networks based on the large-scale location in which the user profiles and content are obtained was used.

Location recommendation, cold-start problem, explicit feedback ,regularized matrix

"CEFFICIENT DATA AWARE COLLOBRATIVE FILTERING FOR LOCATION RECOMMENDATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.254-260, March-2019, Available :http://www.jetir.org/papers/JETIRAU06037.pdf

"CEFFICIENT DATA AWARE COLLOBRATIVE FILTERING FOR LOCATION RECOMMENDATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp254-260, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06037.pdf