Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.eswa.2012.08.054 | Expert Syst. Appl. |
Keywords | Field | DocType |
top k seller,suitable seller,different option,open market,selected trustworthy seller,decision tree,online store,classification technique,personalized trustworthy seller recommendation,recommendation system,data mining | Recommender system,Decision tree,World Wide Web,Open market operation,Computer science,Trustworthiness,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
40 | 4 | 0957-4174 |
Citations | PageRank | References |
3 | 0.38 | 36 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seungsup Lee | 1 | 3 | 0.38 |
| Keunho Choi | 2 | 153 | 10.18 |
| Yongmoo Suh | 3 | 170 | 13.50 |