Mining Negative Comment Data of Microblog Based on Merge-AP
Joint Authors
Chen, Zhijun
Jin, Weijian
Mu, Shibiao
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-25
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
A new depiction method based on the merge-AP algorithm is proposed to effectively improve the mining accuracy of negative comment data on microblog.
In this method, we first employ the AP algorithm to analyze negative comment data on microblog and calculate the similarity value and the similarity matrix of data points by Euclidean distance.
Then, we introduce the distance-based merge process to solve the problem of poor clustering effect of the AP algorithm for datasets with the complex clustering structure.
Finally, we compare and analyze the performance of K-means, AP, and merge-AP algorithms by collecting the actual microblog data for algorithm evaluation.
The results show that the merge-AP algorithm has good adaptability.
American Psychological Association (APA)
Chen, Zhijun& Jin, Weijian& Mu, Shibiao. 2020. Mining Negative Comment Data of Microblog Based on Merge-AP. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1202428
Modern Language Association (MLA)
Chen, Zhijun…[et al.]. Mining Negative Comment Data of Microblog Based on Merge-AP. Mathematical Problems in Engineering No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1202428
American Medical Association (AMA)
Chen, Zhijun& Jin, Weijian& Mu, Shibiao. Mining Negative Comment Data of Microblog Based on Merge-AP. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1202428
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202428