Abstract
Complaint orders in mobile customer service are the records of complaint description, which professional knowledge and information on customer’s complaint intention are kept. Complaint orders classification is important and necessary to be established and completed for further mining, analysis and improve the quality of customer service. Constructed corpus is the basis of research. The lack of complaint orders classification corpus (COCC) in mobile customer service has limited the research of complaint orders classification. This paper first employs K-means algorithm and professional knowledge to determine complaint orders classification labels. Then we craft the annotation rules for complaint orders, and then construct complaint orders classification corpus. The corpus consists of 130044 complaint orders annotated. Finally, we statistically analyze the corpus constructed, and the agreement of each question class reaches over 91%. It indicates that the corpus constructed could provide a great support for complaint orders classification and specialized analysis.
Keywords
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- 1.
Available at https://www.mturk.com/.
- 2.
Available at https://www.crowdflower.com.
- 3.
Available at https://github.com/HIT-SCIR/ltp.
- 4.
Available at https://code.google.com/p/word2vec/.
- 5.
Available at https://github.com/zhng1200/COCC.
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Xu, J. et al. (2018). The Research and Construction of Complaint Orders Classification Corpus in Mobile Customer Service. In: Zhang, M., Ng, V., Zhao, D., Li, S., Zan, H. (eds) Natural Language Processing and Chinese Computing. NLPCC 2018. Lecture Notes in Computer Science(), vol 11109. Springer, Cham. https://doi.org/10.1007/978-3-319-99501-4_31
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DOI: https://doi.org/10.1007/978-3-319-99501-4_31
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