TY  -  
T1  - Entity Recommendation for Everyday Digital Tasks 
SN  -  /  
UR  - http://hdl.handle.net/10138/334390 
T3  -  
A1  - Jacucci, Giulio; Daee, Pedram; Vuong, Tung; Andolina, Salvatore; Klouche, Khalil; Sjöberg, Mats; Ruotsalo, Tuukka; Kaski, Samuel 
A2  -  
PB  -  
Y1  - 2021 
LA  - eng 
AB  - Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realist... 
VO  -  
IS  -  
SP  -  
OP  -  
KW  - Proactive search; user intent modeling; RELEVANCE FEEDBACK; INFORMATION; SEARCH; 113 Computer and information sciences 
N1  -   
PP  -  
ER  -