User-Model-Based Evaluation for Interactive Image Retrieval

Author(s):  
Masashi Inoue ◽  
Manh Hong Nguyen
2008 ◽  
Vol 178 (22) ◽  
pp. 4301-4313 ◽  
Author(s):  
Woo-Cheol Kim ◽  
Ji-Young Song ◽  
Seung-Woo Kim ◽  
Sanghyun Park

2015 ◽  
Vol 713-715 ◽  
pp. 1530-1533
Author(s):  
Yuan Zi He

Personalized recommendation offers a new way to solve the problem of information overload. In order to effectively build user model and improve the effect of personalized recommendation, this paper proposes a novel model for mining contextual information of non-structure text, and insects the contextual information into user model, which enriches user model. The experiment results shown that the model can greatly improve the recommendation performance when the model is applied to contextual data of the recommender system in hotel.


2013 ◽  
Vol 756-759 ◽  
pp. 2047-2050
Author(s):  
Wen Yan Rui ◽  
Hai Ying Mi

This paper analyzes the structure of the whole system, namely, how different users according to their own characteristics of its initiative to provide users with relevant information and content and to establish individual user model, based on user behavior to build personalized user model.


Author(s):  
Seong-Yong Koo ◽  
Kiru Park ◽  
Hyun Kim ◽  
Dong-Soo Kwon

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