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ENSEMBLE OF MULTIPLE kNN CLASSIFIERS FOR SOCIETAL RISK CLASSIFICATION
Chen, Jindong1,2; Tang, Xijin1
2017-08-01
Source PublicationJOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING
ISSN1004-3756
Volume26Issue:4Pages:433-447
AbstractSocietal risk classification is a fundamental and complex issue for societal risk perception. To conduct societal risk classification, Tianya Forum posts are selected as the data source, and four kinds of representations: string representation, term-frequency representation, TF-IDF representation and the distributed representation of BBS posts are applied. Using edit distance or cosine similarity as distance metric, four k-Nearest Neighbor (kNN) classifiers based on different representations are developed and compared. Owing to the priority of word order and semantic extraction of the neural network model Paragraph Vector, kNN based on the distributed representation generated by Paragraph Vector (kNN-PV) shows effectiveness for societal risk classification. Furthermore, to improve the performance of societal risk classification, through different weights, kNN-PV is combined with other three kNN classifiers as an ensemble model. Through brute force grid search method, the optimal weights are assigned to different kNN classifiers. Compared with kNN-PV, the experimental results reveal that Macro-F of the ensemble method is significantly improved for societal risk classification.
KeywordSocietal risk classification Tianya Forum k-Nearest Neighbor ensemble Paragraph Vector
DOI10.1007/s11518-017-5346-4
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFB1000902] ; National Natural Science Foundation of China[61473284] ; National Natural Science Foundation of China[71601023] ; National Natural Science Foundation of China[71371107]
WOS Research AreaOperations Research & Management Science
WOS SubjectOperations Research & Management Science
WOS IDWOS:000406766700003
PublisherSPRINGER HEIDELBERG
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/26346
Collection系统科学研究所
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.China Aerosp Acad Syst Sci & Engn, Beijing 100048, Peoples R China
Recommended Citation
GB/T 7714
Chen, Jindong,Tang, Xijin. ENSEMBLE OF MULTIPLE kNN CLASSIFIERS FOR SOCIETAL RISK CLASSIFICATION[J]. JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING,2017,26(4):433-447.
APA Chen, Jindong,&Tang, Xijin.(2017).ENSEMBLE OF MULTIPLE kNN CLASSIFIERS FOR SOCIETAL RISK CLASSIFICATION.JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING,26(4),433-447.
MLA Chen, Jindong,et al."ENSEMBLE OF MULTIPLE kNN CLASSIFIERS FOR SOCIETAL RISK CLASSIFICATION".JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING 26.4(2017):433-447.
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