Towards a hybrid approach of Primitive Cognitive Network Process and Self-Organizing Map for computer product recommendation

Vincent Qi Chen, Kevin Kam Fung Yuen*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

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 languageEnglish
Title of host publicationProceedings of 2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages9-12
Number of pages4
ISBN (Electronic)9781479975334
DOIs
Publication statusPublished - 21 May 2015
Event2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015 - Harbin, China
Duration: 17 Jan 201518 Jan 2015

Publication series

NameProceedings of 2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015

Conference

Conference2015 International Conference on Intelligent Computing and Internet of Things, ICIT 2015
Country/TerritoryChina
CityHarbin
Period17/01/1518/01/15

Keywords

  • Cognitive Network Process
  • Recommender System
  • Self-organizing Map

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