Semantic-Driven Information Recommendation System
Zhen Huang, Qiang Fang · Applied Mechanics and Materials · 2013
Information recommendation systems is the one of the most effective tools to solve the problem of information overload. In this paper, we design SIRSCA, a semantic-driven information recommendation system under cloud architecture. SIRSCA mainly includes four modules: semantics representation of foundation data and user preference informations; indexing mechanism of massive semantic informations under cloud architecture; recommendation approaches based on semantic computation theory; and technologies of dynamic migration under cloud architecture.