An auto is a vehicle designed for the transport. The most common definition of an auto states that they are wheeled vehicles used for transportation, usually seat four people, carry one or two persons, and generally transport individuals rather than goods. The earliest models of automobiles did not have windows and were locked to protect the occupants from thieves. Over time, however, the automobile has evolved into a versatile vehicle capable of transporting many types of people and goods.
When an individual purchases a vehicle the name of the automobile is entered in a data field called an auto keyword. This data field stores the data required to locate, purchase, and insure the automobile. In order to find this type of auto keyword, an internet search for the model and year of the car is initiated. The auto keyword is then searched in search engines for keywords that are associated with the model and year.
Auto financing refers to financing arrangements for purchasing a new or used car. Auto financing usually takes the form of a loan with a financial institution such as a bank. There are many different types of auto financing. Auto financing can take many forms including dealerships offering car loans, banks providing car loans, and auto dealerships offering lease financing. In addition, there are many independent lending companies that offer non-financial auto financing.
Data types include variables like the credit rating of the prospective borrower, the monthly payment, the age and value of the automobile to be financed, the amount of down payment, the trade-in value and the credit history of the borrower. In order to access the data type used in this example, the internet was used. Using the query string “model: Edmunds” the search returned searches that contained the names of all dealerships selling the model in question. The next step was to determine the best financing option for the borrower. In this example, we used the data type inference to find the best possible vehicle loan to finance the purchase.
Another data type returned was the exact auto keyword for the borrower. The auto keyword is an exact phrase that is searched based on the customer’s name. This data type contains strings of words that describe attributes of the vehicle being sought. In this case, the dealer searched for the exact phrase “cheap cars Toyota Tacoma” and returned four matching results, all of which had positive customer reviews.
Using the data type inference again, we were able to eliminate the Toyota Tacoma from the list of options and chose the best possible financing option for the buyer. Using the same technique as previously mentioned, we eliminated the data that did not have a significant positive rating. We then calculated the percentage of positive customer reviews that came from the four search results returned by the data type inference. This percentage indicated the quality of the online lending. The final result of the Auto Shopping Engine was a total of 4.4 percent positive reviews for each of the four results.