Publication Type : Journal Article
Publisher : Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Source : International Journal of Engineering and Advanced Technology
Url : https://doi.org/10.35940/ijeat.e1095.0785s319
Campus : Haridwar
School : School of Computing
Year : 2019
Abstract : Recommender system is an data retrieval system that gives customers the recommendations for the items that a customer may be willing to have. It helps in making the search easy by sorting the huge amount of data.We have progressed from the era of paucity to the new era of plethora due to which there is lot of development in the recommender system. In today’s scenario the interaction between the groups of friends, family or colleagues has increased due to the advancement in mobile devices and the social media. So, group recommendation has become a necessity in all kinds of domains. In this paper a system has been proposed using the group recommendation system based on hybrid based filtering method to overcome the cold start user issue which arises when a new user signs in and he/she doesn’t have any past records. So, the recommender system does not have enough information related to the user to recommend an item which will be of his/her interest. The dataset has been taken from the MovieLens is used in the experiment.
Cite this Research Publication : , Harleen Kaur, Gourav Bathla, , Group Recommendation for Cold Start Users Using Hybrid Recommendation Technique, International Journal of Engineering and Advanced Technology, Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP, 2019, https://doi.org/10.35940/ijeat.e1095.0785s319