• ANURAG SINGH
• Dr. SUBHADRA SHAW

Recommender systems have to deal with cold start problems as new users and new items are always present, where systems are unable to recommend relevant items to the users due to the unavailability of adequate information about them. In literature, many researchers have addressed this problem by collecting missing information, but their approaches differ in the way they collect missing information. This paper tries to propose a concept to solve the cold start problem by combing collaborative filtering, demographic approach, and click steam visit count.

Recommendation system, clickstream, collaborative filtering, demographic analysis.

"A study to the cold start problem based on click stream data in the recommender system.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 8, page no.86-90, August-2020, Available :http://www.jetir.org/papers/JETIREF06013.pdf

"A study to the cold start problem based on click stream data in the recommender system.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 8, page no. pp86-90, August-2020, Available at : http://www.jetir.org/papers/JETIREF06013.pdf