| 引用本文: | 史殿习,杨若松,莫晓赟,等.日常交互中朋友关系强度度量方法.[J].国防科技大学学报,2017,39(3):77-84.[点击复制] |
| SHI Dianxi,YANG Ruosong,MO Xiaoyun,et al.Measuring method for friend relationship strength in daily communication[J].Journal of National University of Defense Technology,2017,39(3):77-84[点击复制] |
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| 日常交互中朋友关系强度度量方法 |
| 史殿习, 杨若松, 莫晓赟, 李寒, 赵邦辉 |
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(国防科技大学 计算机学院， 湖南 长沙 410073)
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| 摘要: |
| 针对如何度量日常生活中人们之间的关系强度问题展开研究，提出一个从日常轨迹、语义位置以及语义标签三个层次度量朋友之间关系强度的层级模型FRSHV。采用动态时间规整模型通过计算朋友之间的空间距离来度量其日常轨迹之间的相似度，进而使用轨迹序列熵值对用户每天轨迹的相似度进行加权处理，将其作为朋友之间的关系强度；采用主题模型隐含狄利克雷分布分别计算朋友之间的基于语义位置和语义标签的行为模式的相似性，将其作为朋友之间的关系强度；采用集成学习的思想对三个层次的度量结果进行投票，以投票结果作为最终的朋友之间的关系强度。在公开数据集上对FRSHV模型的有效性进行实验验证，结果表明该模型能够有效地度量朋友之间的关系强度。 |
| 关键词: 关系强度 轨迹相似度 动态时间校正 熵 潜狄利克雷分布 投票 |
| DOI：10.11887/j.cn.201703013 |
| 投稿日期：2016-02-10 |
| 基金项目:国家自然科学基金资助项目（61202117，91118008） |
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| Measuring method for friend relationship strength in daily communication |
| SHI Dianxi, YANG Ruosong, MO Xiaoyun, LI Han, ZHAO Banghui |
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(College of Computer， National University of Defense Technology, Changsha 410073, China)
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| Abstract: |
| The FRSHV(friend relationship strength hierarchy vote), a hierarchical model, was proposed to measure the friend relationship strength by user′s daily moving track, semantic positions and the corresponding semantic labels. The daily track similarity was measured by dynamic time warping model using the spatial distance between friends, and the results were then weighed by the entropy of track series. The similarities of friend′s behavior patterns were inferred by latent Dirichlet allocation topic model, respectively using semantic positions and the corresponding semantic labels. Finally, these three similarity results were voted for the ultimate relationship strength. The FRSHV was evaluated by using an open dataset and the results proved the validity of the model in inferring friend′s relationship strength. |
| Keywords: relationship strength trajectory similarity dynamic time warping entropy latent Dirichlet allocation vote |
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