Abstract—This paper, we present Decision Support Systems (DSS) for used car selection using k-nearest neighbor (k-NN) algorithm. This system presents a user-friendly web-based spatial decision support system aimed for selling vehicle. There are two functions that are searching using k-nearest neighbor algorithm, and searching in the database to find one or more matching datasets with the user query. For a web search query, records contain vehicle type, brand, model, year, size, prince and type of engine. By contrast, k-nearest neighbor was estimated from data normalized of the training data set. The result showed that (DSS) present highly effective and sustainable tools for searching vehicle.
Index Terms—K-nearest neighbor algorithm, normalized, search query, web application.
The authors are with Department of Computer Science, Faculty of Informatics, Mahasarakham University, Thailand.
Cite: Sasitorn Kaewman, Wallapa Khemsanthia, Oratai Boongomud, and Chatklaw Jareanpon, "Online Decision Support System of Used Car Selection Using K-Nearest Neighbor Technique," International Journal of Future Computer and Communication vol. 1, no. 2, pp. 164-166, 2012.