Intelligent Recommendation System for Automotive Parts Assembly
This study proposed a method of developing an intelligent recommendation system for automotive parts assembly. The proposed system will display the detailed information and the list components which make up the relevant part that an user wants through the database using the ontology when selecting an automotive part that an user intends to learn or to be guided of. The intelligent recommendation system for parts is offered to users through determining the automatic recommendation order between parts using the weights. This study has experimented the principles of the recommendation system and the method of setting the weights by setting two scenarios.
KeywordsIntelligent recommendation system Automotive parts Weight
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012-0006911).
- 1.Suh HJ, Kim YH, Lee SW, Lee JS (2009) e-learning technology based on mixed reality. Electron Telecommun Trends 24(1)Google Scholar
- 2.Kim Y, Kim J (2011) Attack detection in recommender systems using a rating stream trend analysis. J Korea Soc Internet Inf 12(2):85–101Google Scholar
- 3.Nguyen NT (2007) Computational collective intelligence. Semantic web, social networks and multiagent systems. In: ICWS 2007, pp 1164–1167Google Scholar
- 4.Herlocker JL, Konstan JA, Riedl J (2000) Explaining collaborative filtering recommendations. In: CSCW’’00, 2–6 Dec 2000, PhiladelphiaGoogle Scholar
- 5.Kim G-J, Han J-S (2012) Application method of task ontology technology for recommendation of automobile parts. J Digit Policy Manag 10(6):275–282Google Scholar