%A He Yue,Feng Yue,Zhao Shupeng,Ma Yufeng %T Recommending Contents Based on Zhihu Q&A Community: Case Study of Logistics Topics %0 Journal Article %D 2018 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2018.0088 %P 42-49 %V 2 %N 9 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4550.shtml} %8 2018-09-25 %X

[Objective] This research analyzes the social behaviors of Zhihu (https://www.zhihu.com/) users, aiming to recommend relevant contents more effectively. [Methods] First, we proposed a content recommendation method based on association rules-LDA topic model. Then, we constructed a network of shared sub-topics for specific topics and extracted keywords of the sub-topics with the LDA model. Finally, we pushed contents of the relevant topics for the users. [Results] Our study found that many sub-topics with high degrees of cooccurrence under the topic of logistics, and their confidence levels were above 65%. [Limitations] More comprehensive data is needed in future studies.[Conclusions] The association rule-LDA model provides new directions for content recommendation.