计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2015年
6期
132-137
,共6页
邻居筛选%用户特征%优先项目集%评分邻居优先
鄰居篩選%用戶特徵%優先項目集%評分鄰居優先
린거사선%용호특정%우선항목집%평분린거우선
collaborative filtering%neighbor screening%users’ characteristic%prefer set%rating neighbors’ priority
为了解决协同过滤算法用户邻居筛选的优化问题，提高推荐结果的准确性，提出了一种分步筛选邻居的协同过滤改进算法。该算法首先采用改进的 Pearson 系数法计算用户间的相似度，降序排列后，计算用户特征值，大于用户特征阈值的用户进入下一层筛选；然后选择对优先项目集有过评分的用户形成最终的邻居集；最后进行预测评分得到推荐。实验结果表明，该算法能够有效地获取用户最近邻居集，改善准确性，并且稳定性良好。
為瞭解決協同過濾算法用戶鄰居篩選的優化問題，提高推薦結果的準確性，提齣瞭一種分步篩選鄰居的協同過濾改進算法。該算法首先採用改進的 Pearson 繫數法計算用戶間的相似度，降序排列後，計算用戶特徵值，大于用戶特徵閾值的用戶進入下一層篩選；然後選擇對優先項目集有過評分的用戶形成最終的鄰居集；最後進行預測評分得到推薦。實驗結果錶明，該算法能夠有效地穫取用戶最近鄰居集，改善準確性，併且穩定性良好。
위료해결협동과려산법용호린거사선적우화문제，제고추천결과적준학성，제출료일충분보사선린거적협동과려개진산법。해산법수선채용개진적 Pearson 계수법계산용호간적상사도，강서배렬후，계산용호특정치，대우용호특정역치적용호진입하일층사선；연후선택대우선항목집유과평분적용호형성최종적린거집；최후진행예측평분득도추천。실험결과표명，해산법능구유효지획취용호최근린거집，개선준학성，병차은정성량호。
To increase the accuracy of the neighbor screening in collaborative filtering algorithm, an improved system—collaborative filtering with step screening neighbors (SSN-CF)—is proposed in this paper. This algorithm firstly uses an improved Pearson method to compare the similarity between users. After arranging the data in descending order, the uses’ characteristic value is calculated. Only those who surpass the threshold value are selected. Then the system gathers the users who graded the priority set to make up the final neighbor set. Finally the users’ grades are estimated and recommendation is made. Experiments have shown that the algorithm can effectively get the most similar neighbor set of target uses. Meanwhile, it is tested that accuracy and stability is improved.
