Conversational Sentiment Quadruple Extraction

Conversational Sentiment Quadruple Extraction is a technique in the field of Natural Language Processing aimed at extracting sentiment quadruples from conversational data, which include the subject, object, sentiment polarity, and sentiment intensity. The goal of this technology is to accurately identify and quantify emotional information in conversations, providing more granular data support for sentiment analysis. Its application value lies in helping businesses gain a deeper understanding of customer emotions, optimize products and services, and enhance user experience and satisfaction.