The Design of Web Based Car Recommendation System using Hybrid Recommender Algorithm

  • Authors

    • Leyo Babu Thomas
    • V Vaidhehi
    2018-06-25
    https://doi.org/10.14419/ijet.v7i3.4.16772
  • Collaborative Filtering algorithm, Recommendation system, Item profile, User model, Hybrid recommender system

  • Abstract

    Web based recommendations for any item is mandatory in E-commerce based web sites. This paper is about the design of web based car recommendation system using the hybrid recommender algorithm. The proposed hybrid recommender algorithm is the combination of user-to-user and item-to-item collaborative filtering method to generate the car recommendations. The user model is designed using demographic features, click data and browsing history. Item profile is built using the various attributes of car, 40 brands of car including 224 car types are used in this work. The synthetic dataset of 300 users with 10000 sessions is used to build user model. The proposed algorithm is evaluated with 100 real time users and shows the 83% accuracy in generating recommendations.

     

     

  • References

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  • How to Cite

    Babu Thomas, L., & Vaidhehi, V. (2018). The Design of Web Based Car Recommendation System using Hybrid Recommender Algorithm. International Journal of Engineering & Technology, 7(3.4), 192-196. https://doi.org/10.14419/ijet.v7i3.4.16772

    Received date: 2018-08-03

    Accepted date: 2018-08-03

    Published date: 2018-06-25