A Cognitive Computing Approach for Classification of Complaints in the Insurance Industry

2017 International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Forster, J.^1,2 ; Entrup, B.^2

Department for Computer Sciences and Mathematics, University of Applied Sciences Munich, Lothtraße 64, Munich

80335, Germany^1

Global Business Services, IBM Germany, IBM-Allee 1, Ehningen

71139, Germany^2

关键词: Cognitive Computing;    F1 scores;    Insurance companies;    Insurance industry;    Language modelling;    Multi-label text classification;    Natural languages;    Text classification;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/261/1/012016/pdf
DOI  :  10.1088/1757-899X/261/1/012016

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

In this paper we present and evaluate a cognitive computing approach for classification of dissatisfaction and four complaint specific complaint classes in correspondence documents between insurance clients and an insurance company. A cognitive computing approach includes the combination classical natural language processing methods, machine learning algorithms and the evaluation of hypothesis. The approach combines a MaxEnt machine learning algorithm with language modelling, tf-idf and sentiment analytics to create a multi-label text classification model. The result is trained and tested with a set of 2500 original insurance communication documents written in German, which have been manually annotated by the partnering insurance company. With a F1-Score of 0.9, a reliable text classification component has been implemented and evaluated. A final outlook towards a cognitive computing insurance assistant is given in the end.