Topic-aware staff learning material generation in complaint management systems

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.

Recommender systems to support learners’ Agency in a Learning Context: a systematic review

“…The results were also positive for articles that did not describe a comparison (Dascalu et al, 2015;Guangjie, Junmin, Meng, Yumin, & Chen, 2018). Some of them were also prospective, like Drachsler et al (2010), who presented the participant's ideas for future developments regarding, among other things, privacy and the possibility of rating the recommendations they received.…”