Using Heterogeneous Social Media As Auxiliary Information to Improve Car Recommendation Performance
International Journal of Emerging Technology and Innovative Engineering Volume 5, Issue 3, March 2019
6 Pages Posted: 7 May 2019
Date Written: March 10, 2019
Knowledge about current user preferences and needs regarding electric vehicles is key for developing convenient solutions in the field of e-mobility. They are decisive for a successful market uptake of car.A great number of people have used social media platforms such as Twitter to develop a car recommendation system. Here, we propose a Twitter-based recommendation system via the aid of heterogeneous social media.The collected tweets is processes with NLP to extract the keywords. On the other hand, an analytical user posting behavior algorithm (APBA) is created for establishing users’ posting behavior vectors (Vpb) based on earlier posts in Twitter.Behavior vectors is classified into Fuzzy Bag of Words with classification accuracy of 96.7% using the proposed model. (FBoW).
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