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Fuzzy Output Support Vector Machine Based Incident Ticket Classification

Libo YANG

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Summary :

Incident ticket classification plays an important role in the complex system maintenance. However, low classification accuracy will result in high maintenance costs. To solve this issue, this paper proposes a fuzzy output support vector machine (FOSVM) based incident ticket classification approach, which can be implemented in the context of both two-class SVMs and multi-class SVMs such as one-versus-one and one-versus-rest. Our purpose is to solve the unclassifiable regions of multi-class SVMs to output reliable and robust results by more fine-grained analysis. Experiments on both benchmark data sets and real-world ticket data demonstrate that our method has better performance than commonly used multi-class SVM and fuzzy SVM methods.

Publication
IEICE TRANSACTIONS on Information Vol.E104-D No.1 pp.146-151
Publication Date
2021/01/01
Publicized
2020/10/14
Online ISSN
1745-1361
DOI
10.1587/transinf.2020EDP7044
Type of Manuscript
PAPER
Category
Artificial Intelligence, Data Mining

Authors

Libo YANG
  North China University of Water Resources and Electric Power

Keyword