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Research on Real-time Personalized Recommendation Algorithm
보안공학연구지원센터(IJUNESST) International Journal of u- and e- Service, Science and Technology Vol.7 No.5 2014.10 pp.359-368
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
Personalized recommendation algorithm is core to recommendation systems, which matters the quality of recommendations of such system. The paper proposed an improved Slope one recommendation algorithm, M-Slope one. Based on real-time user interest model, the new method can calculate similarities between users and establish neighboring user groups to narrow down search scope of related items and improve the average rating differential equation for items. The algorithm proves its effectiveness for improving the precision of recommendations.
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