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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (9): 42-49    DOI: 10.11925/infotech.2096-3467.2018.0088
Current Issue | Archive | Adv Search |
Recommending Contents Based on Zhihu Q&A Community: Case Study of Logistics Topics
Yue He,Yue Feng,Shupeng Zhao(),Yufeng Ma
Business School, Sichuan University, Chengdu 610064, China
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[Objective] This research analyzes the social behaviors of Zhihu ( 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.

Key wordsZhihu      Association Rule      LDA      Content Recommendation     
Received: 18 January 2018      Published: 25 October 2018

Cite this article:

Yue He,Yue Feng,Shupeng Zhao,Yufeng Ma. Recommending Contents Based on Zhihu Q&A Community: Case Study of Logistics Topics. Data Analysis and Knowledge Discovery, 2018, 2(9): 42-49.

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