The Impact of Customer Service on Telemarketing Success

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. Methods and techniques for search-based models. These models extract relevant information from a text corpus . And then generate answers based on the resulting documents. Generative models. These models generate responses . From scratch using an understanding of the language and context of the request. Hybrid models. . These models combine search methods and generative methods to achieve better performance. Knowledge graph a . Knowledge graph is a structured representation of information that can be used to improve the .


Accuracy and relevance of a system. Challenges and greece whatsapp data future directions data quality the quality of . The training data used to develop a system is critical to its performance. Ensuring the . Accuracy, diversity and representativeness of data is a major challenge. Contextual understanding systems often have . Difficulty understanding the context of a request, especially when it involves ambiguity or multiple interpretations. . Bias and fairness systems can become biased if training data or algorithms are not carefully . Designed.


An important consideration is to eliminate bias and ensure fairness. Interpretability. Understanding how a . System arrives at an answer can be difficult. Developing methods to explain why a system . Reacts is an active area of ​​research. Example of successful application in customer support for . Lead generation. A large e-commerce company implemented a powerful chatbot to handle customer queries. A . Chatbot can answer a wide range of questions, reducing customer support costs and increasing customer .