Name
Abstract | ||
|---|---|---|
It is a challenge to provide an intelligent product suggestion for these new customers without previous shopping records in the supermarket application. To solve such a problem, we design a hybrid fuzzy expert system for recommendation using the improved fuzzy prototype model and semantic distance. Moreover, we implement a demonstration of the recommendation system by using intelligent Fril/SQL interrogator, which is an object-oriented and knowledge-based support query system containing the set of reusable logic objects linking one another. The results are evaluated by comparing the average product frequency of recommendations with the average frequency of non-recommendations. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.is.2006.10.007 | Inf. Syst. |
Keywords | Field | DocType |
new customer,intelligent product suggestion,average frequency,knowledge-based support query system,recommendation system,hybrid fuzzy expert system,intelligent fril,sql interrogator,improved fuzzy prototype model,semantic distance,average product frequency,object oriented,recommender system,knowledge base | Data mining,Fuzzy classification,Computer science,Fuzzy set operations,Artificial intelligence,Fuzzy control system,Adaptive neuro fuzzy inference system,Semantic similarity,SQL,Neuro-fuzzy,Fuzzy logic,Machine learning,Database | Journal |
Volume | Issue | ISSN |
32 | 7 | Information Systems |
Citations | PageRank | References |
3 | 0.43 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dong (Walter) Xie | 1 | 4 | 1.14 |
| Jim F. Baldwin | 2 | 17 | 1.70 |