A large portion of the car-buying experience in the United States involves interactions at a car dealership. At the dealership, the car-buyer relays their needs to a sales representative. However, most car-buyers are only have an abstract description of the vehicle they need. Therefore, they are only able to describe their ideal car in "car-speak". Car-speak is abstract language that pertains to a car's physical attributes. In this paper, we define car-speak. We also aim to curate a reasonable data set of car-speak language. Finally, we train several classifiers in order to classify car-speak.
@article{arxiv.2002.02070,
title = {Understanding Car-Speak: Replacing Humans in Dealerships},
author = {Habeeb Hooshmand and James Caverlee},
journal= {arXiv preprint arXiv:2002.02070},
year = {2020}
}