Title: Topic-aware staff learning material generation in complaint management systems

Authors: Li Guangjie; Ling Junmin; Shengguang Meng; Liao Yumin; Wei Chen

Addresses: China Mobile Group Guangxi Company Limited, Nanning, China ' China Mobile Group Guangxi Company Limited, Nanning, China ' Zhuhai Faster Software Technology Co., Ltd, Zhuhai, China ' Zhuhai Faster Software Technology Co., Ltd, Zhuhai, China ' Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, China

Abstract: In this paper, a topic-aware staff learning material generation approach is proposed in complaint management systems. Historical processing logs are extracted to form a complaint space. Complaint processing skills of staff members are assessed in terms of quantity, efficiency and quality on various topics. Similar staff members are clustered according to their behavioural characteristics. A resource recommendation algorithm is proposed to recommend complaint processing records from highly skilled colleagues in the cluster for the staff member to learn. Preliminary experiment results show good performance of the proposed method.

Keywords: user modelling; staff learning; user clustering; complaint management system.

DOI: 10.1504/IJIL.2018.088786

International Journal of Innovation and Learning, 2018 Vol.23 No.1, pp.93 - 103

Received: 04 Aug 2016
Accepted: 04 Feb 2017
Published online: 19 Dec 2017 *

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