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篇名 |
Attribute Inference by Link Strength Modeling in Online Social Networks with User Tags
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並列篇名 | Attribute Inference by Link Strength Modeling in Online Social Networks with User Tags |
作者 | Ya Xiao、Zhijie Fan、Chengxiang Tan、Qian Xu、Wenye Zhu |
英文摘要 | The link strength between two users in online social networks is generally latent and can not be observed directly. The strength is usually related to the interests, behaviors, posted texts, common friends, and common followings of two users. Most previous works have ignored the distinctions of the link strengths among different pairs of users, and some works simply classify the relationships into strong and weak instead of a particular value. Given the importance of link strength in link prediction or item recommendation system, in this paper, we propose a novel method for modeling the strength of links in social networks by jointly taking the common friends, common followings, user behaviors, and user tags into consideration. A new method to construct the tags for each user based on the semantics of open information is also presented. The attribute inference and tag prediction approach based on link strength is put forward and evaluated by the experiments on a real-world dataset, the inferred results prove the feasibility of the proposed model and demonstrate that the model substantially outperforms the compared methods. |
起訖頁 | 689-699 |
關鍵詞 | Social networking、Link strength、Attribute inference、User behaviour、Tags |
刊名 | 網際網路技術學刊 |
期數 | 202005 (21:3期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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