To handle more complex or ambiguous customer complaints, the RE-GrievanceAssist pipeline can be extended in several ways:
Dynamic Issue Classification: Implement a dynamic issue classification system that can adapt and learn from new data. This can involve using techniques like active learning to continuously improve the classification models based on feedback from manual interventions.
Natural Language Understanding: Incorporate natural language understanding (NLU) models to better interpret the nuances and context of customer complaints. This can help in identifying underlying issues even if they do not fit neatly into predefined categories.
Hierarchical Classification: Enhance the hierarchical classification approach by introducing more levels of hierarchy to capture finer distinctions in customer complaints. This can help in handling complex complaints that may involve multiple interconnected issues.
Feedback Loop: Implement a feedback loop mechanism where manual interventions and feedback from agents are used to refine the classification models. This continuous learning process can improve the system's ability to handle diverse and ambiguous complaints effectively.