A comparability of two cutting-edge dynamic subject fashions fixing client complaints classification train
Buyer evaluations about services present worthwhile details about buyer satisfaction. They supply perception into what must be improved throughout the entire product improvement. Dynamic subject fashions in enterprise intelligence can establish key product qualities and different satisfaction elements, cluster them into classes, and consider how enterprise selections materialized in buyer satisfaction over time. That is extremely worthwhile info not just for product managers.
This text will examine two of the newest subject fashions to categorise buyer complaints knowledge. BERTopic by Maarten Grootendorst (2022) and the current FASTopic by Xiaobao Wu et al. (2024) introduced finally yr’s NeurIPS, are the present main fashions for subject analytics of buyer knowledge. For these fashions, we’ll discover in Python code:
- how one can successfully preprocess knowledge
- how one can practice a Bigram subject mannequin for buyer grievance evaluation
- how one can mannequin subject exercise over time.
