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.
- Internet computing
- information search and retrieval
- mobile computing
- text mining
ASJC Scopus subject areas
- Computer Networks and Communications