کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
383041 | 660800 | 2013 | 6 صفحه PDF | دانلود رایگان |
Although more and more customers are buying products on online stores, they have a difficulty in selecting a both trustworthy and suitable seller who sells a product they want to buy since there is a plenty number of sellers who sell the same product with different options. Therefore, the objective of this research is to propose a personalized trustworthy seller recommendation system for the customers of an open market in Korea. To that end, we first developed a module which classifies sellers into trustworthy one or not using a classification technique such as decision tree, and then developed another module which makes use of the content-based filtering method to find best-matching top k sellers among the selected trustworthy sellers. Experimental results show that our approach is worthwhile to take. This study makes a contribution at least in that to our knowledge it is the first attempt to recommend sellers, not products as done in most other studies, to customers.
► Customers have a difficulty in selecting a both trustworthy and suitable seller.
► We propose a personalized trustworthy seller recommendation system in open market.
► We develop a module for classifying sellers into trustworthy one or not.
► We develop a module for finding suitable sellers among the trustworthy sellers.
Journal: Expert Systems with Applications - Volume 40, Issue 4, March 2013, Pages 1352–1357