In this thesis project we show how to apply NLP tools to get scores from a vast amount of car reviews.
Download the zip file with all required files from here
To run this tool, you need to have at least version 8 of JRE of JDK. If you want to run this tool from the command line, be sure to have set up the global JAVA_HOME environment variable.
There are two ways to use this tool. First of all, you may simply run the program by double clicking the jar file. Secondly, you may want to use it as an API and pass arguments. To do so, simply run the following line from a terminal:
cd /your/path/to/the/jar java -jar "Car Reviewer V2.jar"This is the minimal way to run the program from the commandline. If no arguments are passed, the GUI is activated by default. To pass arguments, simply append them behind the command provided above. Arguments that can be passed are:
- API or GUI.
- A specific car, for example bmw_x5-edrive_2016. This can be more than one car.
- A number indicating the maximum of shown cars (the top-x output).
- One or more categories. For example quality, mileage, price, or performance.
Note: The arguments passed are not case sensitive with exception of the categories and do not have to be in order. If a category has an uppercase level, it means the whole category gets taken as input instead of just a subcategory.
Let's make this more clear with an example.
Franks wants to buy a high quality car for a good price/value. He does not care much about specifics as long as it is a good overall car. Franks is also an application developer and uses the API. From the commandline he runs:
java -jar "Car Reviewer V2.jar" api Quality price ValueThe output looks like this:
Categories interested in: [Quality, price, Value]
Cars interested in : []
Cadillac xts 2016
Quality: 5.0
Average: 5.0
Mercedes-benz g-class 2016
Quality: 5.0
Average: 5.0
Mercedes-benz e-class 2016
Quality: 5.0
Average: 5.0
Kia sorento 2017
Quality: 5.0
Average: 5.0
Ford transit-connect 2016
Value: 5.0
Average: 5.0
As you can see, all cars look excellent to Frank and because he did not have too many demands, this is only logical.
Let's make it a bit more complicated. Mark, Frank's brother, is looking for a very specific car. What he cares about most if: acceleration, control, handle, transmission, look, engine, seats, safety, mileage, mileage, price, value. The output for him will looks as follows:
java -jar "Car Reviewer V2.jar" api acceleration control handle transmission look engine seats safety mileage mileage price valueCategories interested in: [acceleration, control, handle, transmission, look, engine, seats, safety, mileage, mileage, price, value]
Cars interested in : []
Ford fusion-hybrid 2016
Value: 5.0
Average: 5.0
Volkswagen passat 2016
Value: 4.0
Average: 4.0
Hyundai tucson 2016
Value: 4.0
Average: 4.0
Volvo v60 2016
Value: 4.0
Average: 4.0
Mercedes-benz c-class 2017
Parts: 4.0
Average: 4.0
This output is more interesting as this shows some defects in the program. For one, not all variables are found for each car. This may also be a good thing since no car will have features with all of the variables above. What's more concerning is the reason that why these cars have such high scores: these cars all have 1-3 features. Of course, for a car with 10+ features it is far more difficult to get a high average than a car with only a single high scoring feature. One solution is to add a minimum of features for each car before they can add to the scoreboard.
The data being used here is a json file from Edmunds.com. There are 489 cars with each 1-25 reviews. In total, there are approximately 60,000 words to be analysed, or 120 pages. For this reason, it takes well over half an hour to process all of the data if no cars are specified. The reason that this takes so long is because of Standford's CoreNLP, which takes 99% of the total time to process. The other 1% is to assign categories, calculate sentiment, and group everything together.
- If car has less than x features, do not score
- Use pre-annotated data
- Make extended parameter to show all categories