An Efficient System for Information Recommendation - Zhenhua Huang; Qiang Fang (Institute of Advanced Engineering and Science, 2014)
A recommendation system is the one of the most effective tools for tackling with the problem of information overload. However, as the maturity of Web 2.0 and the emergence of massive information, the existing information recommendation systems have the serious drawbacks in the aspects of real-timing, robustness and self-adaptability. Motivated by the above facts, in this paper, we design SIRSCA, which is an efficient semantic-driven information recommendation system under the cloud architecture. Specially, the SIRSCA system mainly include 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. We present the extensive experiments that demonstrate our improved system is both efficient and effective. DOI: http://dx.doi.org/10.11591/telkomnika.v12i6.5445