Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the problem that there exists item deviation and user preferences in collaborative filtering recommendation for the interaction between factors related in items and users, this paper proposed a recommendation algorithm integrated item deviation and user preference. Firstly it clustered to generate item clusters on LDA topics modeling and to get user clusters by using K-means; then it generated item deviation score on the constraints of item cluster and user cluster, and obtained user preference score with probability transfer on user-item score and item type. Finally it weighted the item deviation score and user preference score linearly to form the prediction score based on the existing scoring average in the item cluster. Comparison experiments show that the new algorithm could obtain reasonable recommendation based on different neighbors and improve recommendation accuracy.
Subjects: Library Science，Information Science >> Information Science submitted time 2017-11-08 Cooperative journals: 《数据分析与知识发现》
Abstract：【目的】分析不同情境因素对用户步行路线规划的影响, 构建用户路线规划的情境模型。【方法】邀请30名用户完成室外步行导航实验, 对用户路线规划的情境和行为进行Spearman 相关性分析和多元线性回归分析。【结果】初始规划阶段, 目的地选择次数越多, 用户搜索时长越长; 对估计时间在意程度越高, 对路线的浏览时长越长。重新规划阶段, 不同性别和年龄的用户其主观时间压力不同; 任务困难度越高时其操作次数反而会减少。【局限】数据处理存在一定的主观性; 实验中其他因素给用户的心理和行为产生潜在影响, 可能会对实验结果造成一定的干扰。【结论】步行路线规划情境模型更关注行为因素, 揭示初始路线规划和重新规划路线的各个情境因素的关系, 为移动地图开发者提供参考价值。
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