• Anu Taneja

Recommendation Systems have gained a wider attention due to large amount of generated data in digital world. The more are the services provided to the users, more are the users in dilemma in choice of the appropriate services. In this situation, recommendation systems play an important role as they suggest services based on user’s interests. This eases the task of user and improves the decision making. Though traditional recommendation systems have succeeded successfully in generation of accurate suggestions but it has been observed that users’ interests changes with time. This issue has prompted the researchers to work towards the direction of temporal recommendation systems. This research study provides the systematic review of temporal recommendation systems including the benefits and challenges faced in this domain. This study would benefit the researchers working in this domain and also e-commerce sectors towards the growth of business.

drift, dynamic, interests, recommendations, temporal models

"Temporal Recommendation Systems: A Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 12, page no.264-268, December-2017, Available :http://www.jetir.org/papers/JETIR1712218.pdf

"Temporal Recommendation Systems: A Review ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 12, page no. pp264-268, December-2017, Available at : http://www.jetir.org/papers/JETIR1712218.pdf