Titlebook: User Modeling, Adaptation and Personalization; 19th International C Joseph A. Konstan,Ricardo Conejo,Nuria Oliver Conference proceedings 20

MEDAL

書目名稱User Modeling, Adaptation and Personalization影響因子(影響力)




書目名稱User Modeling, Adaptation and Personalization影響因子(影響力)學(xué)科排名




書目名稱User Modeling, Adaptation and Personalization網(wǎng)絡(luò)公開度




書目名稱User Modeling, Adaptation and Personalization網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱User Modeling, Adaptation and Personalization被引頻次




書目名稱User Modeling, Adaptation and Personalization被引頻次學(xué)科排名




書目名稱User Modeling, Adaptation and Personalization年度引用




書目名稱User Modeling, Adaptation and Personalization年度引用學(xué)科排名




書目名稱User Modeling, Adaptation and Personalization讀者反饋




書目名稱User Modeling, Adaptation and Personalization讀者反饋學(xué)科排名

EWE

The Impact of Rating Scales on User’s Rating BehaviorIn this paper we present two user studies that investigate the role of rating scales on user’s rating behavior, showing that the rating scales have their own “personality” and mathematical normalization is not enough to cope with mapping among different rating scales.

harpsichord

Console

Conference proceedings 2011m 164 submissions. The tutorials and workshops were organized in topical sections on designing adaptive social applications, semantic adaptive social Web, and designing and evaluating new generation user modeling..

Aggrandize

Modeling Mental Workload Using EEG Features for Intelligent Systemsdata were gathered from 17 participants who performed different cognitive tasks. We also explore the application of our model in a non laboratory context by analyzing the behavior of our model in an educational context. Our findings have implications for intelligent tutoring systems seeking to continuously assess and adapt to a learner’s state.

indecipherable

依法逮捕

手榴彈

Corral

machination

Leveraging Collaborative Filtering to Tag-Based Personalized Searchotations of tags for items from other similar items. We then apply the latency of tags to a tag-based personalized ranking depending on individual users. Experimental results demonstrate the feasibility of our method for personalized searches in social media services.