A Method of Recommending Buy Points Based on Price Patterns
Eun-Sill Jang, Yong-Kyu Lee · Journal of the Korea Society of Computer and Information · 2007
Even though much research has been performed to recommend favorite items to the buyers in the internet shopping mall, to the best of our knowledge. it is hard to find previous research on the recommendation of buy points. In this paper, we propose a method which can be used to recommend buy points of an item to the buyers. To do this, a database containing normalized price patterns is constructed from the archive of past prices. Then, the future price pattern is retrieved from the database based on the similarity. Here, regression analysis is used to find and analyze the elements that affect the price. We also present performance results showing that the proposed method can be useful for shopping malls.