Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Research on Community Knowledge Modeling of Readers Based on Interest Labels

  • Kai, Wang (School of Health Management, Bengbu Medical College) ;
  • Wei, Pan (School of Health Management, Bengbu Medical College) ;
  • Xingzhi, Chen (School of Health Management, Bengbu Medical College)
  • Received : 2022.06.16
  • Accepted : 2022.11.28
  • Published : 2023.02.28
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Abstract

Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

Keywords

Acknowledgement

This work is supported by the Key Project of Humanities and Social Science in Anhui Education Department (Grant No. 2022AH051412 and 2022AH051405), the Major Humanities and Social Science Project of Education Department of Anhui Province (Grant No. SK2021ZD0066), and the Key Project of Humanities and Social Sciences of Bengbu Medical College (Grant No. 2020byzd223sk).

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