欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
针对协同过滤推荐算法面临数据高维稀疏特征时推荐效果较差的缺点,在现有高维稀疏数据聚类研究的基础上,利用评分数据稀疏差异度和项目类别构造集合差异度度量公式,用以在用户—项目评分矩阵上进行项目聚类。在此基础上进行项目相似性计算和最近邻居查询,然后对用户未评分的项目进行评分预测,进而产生推荐。实验证明本文提出的基于稀疏差异度和项目类别的项目聚类算法及在此基础上的协同过滤推荐结果优于传统的K-means聚类算法基础上的推荐效果。同全项目集协同过滤推荐相比较,在效率和推荐精度上也表现出一定的优越性。
同期刊论文项目
同项目期刊论文
Equity and efficiency analysis of pricing strategies in a bi-modal network with heterogeneous user g
Modeling the evolutions of day-to-day route choice and year-to-year ATIS adoption with stochastic us
Modeling time-dependent travel choice problems in road networks with multiple user classes and multi
One-step solution fabrication of magnetic chains consisting of jingle-bell-shaped cobalt mesospheres
Support vector machine forecasting method improved by chaotic particle swarm optimization and its ap
Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and mu
A model for evaluation of transport policies in multimodal n etworks with r oad and p arking capacit
Optimization of time-varying parking charges and parking supply in networks with multiple user class
Using r evenue-sharing contract to improve the supply chain performance Under r etailers’ competitio
The Effectiveness of Revenue-sharing Contract to Coordinate the Price-Setting Newsvendor Products’ S
Analysis of the impact of price-sensitivity factors on the returns policy in coordinating supply cha
位置：