Abstract
Products have similarities which can be analyzed to recommend products to consumers with different preferences. This paper combines Primitive Cognitive Network Process (PCNP) and Self-Organizing Map (SOM) to cluster products into appropriate categories on the basis of consumer preferences and product similarities. PCNP is an ideal alternative of Analytic Hierarchy Process (AHP) to quantify the weights for the attributes used in SOM. To demonstrate the applicability of PCNP-SOM, an example of computer product recommendation is illustrated.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015 |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 9-12 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781479975334 |
| DOIs | |
| Publication status | Published - 21 May 2015 |
| Externally published | Yes |
| Event | International Conference on Intelligent Computing and Internet of Things 2015 - Harbin, China Duration: 17 Jan 2015 → 18 Jan 2015 |
Conference
| Conference | International Conference on Intelligent Computing and Internet of Things 2015 |
|---|---|
| Abbreviated title | ICIT 2015 |
| Country/Territory | China |
| City | Harbin |
| Period | 17/01/15 → 18/01/15 |
Keywords
- Cognitive Network Process
- Recommender System
- Self-organizing Map
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver