Paper Info
Title
EPE: An Embedded Personalization Engine for Mobile Users
Abstract
The proposed embedded personalization engine (EPE) utilizes valuable in-device usage data for inferring mobile user interests in a privacy-preserving manner. To provide users with personalized services, the proposed approach analyzes both the usage data inside a mobile device and service items--such as news articles and mobile apps--using the Open Directory Project (ODP) as a knowledge base. Embedded classification and ranking methodologies effectively match such service items with inferred user interests. The scenario-based evaluation clearly shows that the proposed EPE gives users highly personalized services with both reasonable perceived latency and little energy consumption.
Year
DOI
Venue
2014
10.1109/MIC.2013.124
IEEE Internet Computing
Keywords
Field
DocType
mobile apps,scenario-based evaluation,proposed epe,usage data analysis,embedded classification methodology,proposed approach analyzes,mobile device,knowledge base,data privacy,human factors,ranking methodology,mobile users,odp,pattern classification,personalization engine,mobile user interest,epe,internet computing,usage data,news articles,service items,personalized services,valuable in-device usage data,service item,embedded personalization engine,personalized service,perceived latency,mobile user interests,energy consumption,open directory project,privacy-preserving manner,personal computing,user interest,personalization,proposed embedded personalization engine,mobile computing,information search and retrieval,text mining,engines,internet,computer architecture,mobile communication,servers
Mobile computing,World Wide Web,Computer science,Directory,Server,Computer network,Mobile device,Knowledge base,Usage data,Mobile telephony,Personalization
Journal
Volume
Issue
ISSN
18
1
1089-7801
Citations 
PageRank 
References 
8
1.09
4
Authors
3
Name
Order
Citations
PageRank
JongWoo Ha1556.79
Jung-Hyun Lee218823.59
Sangkeun Lee349865.59