[Objective] This research proposes a method to discover city profile based on semantic mining, aiming to obtain public awareness of the city. [Methods] Firstly, we generated a description framework of the city profile with hierarchical structure based on tags similarity and agglomerative hierarchical clustering. Secondly, we calculated the importance of social tags to reveal semantic features of cities based on latent semantic mining. Finally, we filtered out social tags with high explanation degree of city profile, and integrated them with the description framework of city profile to establish the hierarchical structure. [Results] With users’ reviews from Zhihu, we established the structural city profiles of six provincial capitals from central China, which identified the public perception of these cities. [Limitations] More research is needed to extract high-quality social tags automatically and generate a better description framework for the city profiles. [Conclusions] The proposed method could extract city profiles from massive social tags and develop fine-grained descriptions.
毕崇武,叶光辉,李明倩,曾杰妍. 基于标签语义挖掘的城市画像感知研究 *[J]. 数据分析与知识发现, 2019, 3(12): 41-51.
Chongwu Bi,Guanghui Ye,Mingqian Li,Jieyan Zeng. Discovering City Profile Based on Tag Semantic Mining. Data Analysis and Knowledge Discovery, DOI：10.11925/infotech.2096-3467.2019.0502.
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