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首页> 外文期刊>Procedia Computer Science >Modeling Temporal Dynamics of User Interests in Online Social Networks
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Modeling Temporal Dynamics of User Interests in Online Social Networks

机译:在线社交网络中用户兴趣的时间动态建模

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摘要

Recent years have witnessed an explosive growth of Online Social Networks (OSNs), which serve as a fertile ground for research such as, characterizing individual and group behaviors, identifying information diffusion patterns, and building new recommendation system. This paper explores user interests in social network. While user interests has been extensively studied as the fundamental solution, it neglects the point that a user may change her interests due to social status shift over time. In this paper, we explore two main problems: how user interests change over time and whether user interests have hierarchy. To this end, we first formulate the user interests problem, then adopt semantic enrichment method to determine user interests, and finally employ the topic hierarchy tree model to capture user interests change over time and identify interest hierarchy. Experimental results demonstrate user interests can be divided into primary interest and secondary interest. the primary interest of user hold stability in a long-term period; the secondary interest, however, is more likely to keep up with hot topics or events in the moment. Meanwhile, We also test and compare our model with two existing systems - Who likes what? and TUMS, the result shows that our model can be profiled a more fine-grained user interests.
机译:近年来,在线社交网络(OSN)呈爆炸式增长,为研究(例如表征个人和团体行为,确定信息传播模式以及建立新的推荐系统)提供了沃土。本文探讨了社交网络中的用户兴趣。尽管已经广泛研究了用户兴趣作为基本解决方案,但它忽略了用户可能由于社会地位随时间变化而改变其兴趣这一点。在本文中,我们探讨了两个主要问题:用户兴趣随时间变化以及用户兴趣是否具有层次结构。为此,我们首先提出用户兴趣问题,然后采用语义丰富的方法确定用户兴趣,最后采用主题层次树模型捕获用户兴趣随时间的变化并识别兴趣层次。实验结果表明,用户兴趣可以分为主要兴趣和次要兴趣。用户长期保持稳定的首要利益;然而,次要的兴趣更可能跟上当前热门话题或事件。同时,我们还将测试模型并与两个现有系统进行比较-谁喜欢什么?和TUMS,结果表明我们的模型可以描述更细粒度的用户兴趣。

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