CAJ | 학술논문

为解决传统协同过滤算法中存在的数据稀疏与冷启动问题,社会化信任推荐机制被引入推荐系统,通过加入用户的显式信任信息,可有效地缓解上述问题.但是显式信任较难获取,并且数据较为稀疏,为了更好地提高推荐效率,在基于显式信任的TrustSVD算法的基础上,加入用户的隐式信任信息,提出了一种基于双信任机制的奇异值分解(singular value decomposition,SVD)算法EITrustSVD.在利用显式信任获得可靠推荐的同时,通过隐式信任的影响获得与用户喜好相关的推荐.通过实验证明,该方法可以较好地解决冷启动问题,且能提高推荐的准确率.
위해결전통협동과려산법중존재적수거희소여랭계동문제,사회화신임추천궤제피인입추천계통,통과가입용호적현식신임신식,가유효지완해상술문제.단시현식신임교난획취,병차수거교위희소,위료경호지제고추천효솔,재기우현식신임적TrustSVD산법적기출상,가입용호적은식신임신식,제출료일충기우쌍신임궤제적기이치분해(singular value decomposition,SVD)산법EITrustSVD.재이용현식신임획득가고추천적동시,통과은식신임적영향획득여용호희호상관적추천.통과실험증명,해방법가이교호지해결랭계동문제,차능제고추천적준학솔.
To resolve the problems of data sparsity and cold-start of the collaborative filtering algorithms in recom-mender systems, the trust information has being introduced to recommender systems, it can effectively alleviate these problems above by adding the users'explicit trust information. But the explicit trust information is more diffi-cult to obtain or sparse, in order to better improve the efficiency of recommendation, in the basis of TrustSVD algo-rithm based on explicit trust, this paper introduces the implicit trust information, and proposes a singular value decom-position (SVD) algorithm based on double trust mechanism, named EITrustSVD. At the same time of getting a reli-able recommendation by using the explicit trust, the EITrustSVD algorithm gets a recommendation related to user performance through implicit trust. The experimental results show that the proposed algorithm is a better solution to the problem of cold-start, and has a better recommendation accuracy.