Discourse refers to any linguistic construction with multiple sentences. A disclosure is used in understanding and generating natural language. A variety of text mining applications can be supported by discourse processing, which is a collection of Natural Language Processing (NLP) tasks used to extract linguistic structures from texts at different levels. Identifying the conversational discourse's topic structure, coherence structure, coreference structure, and conversation structure is required for this. Together, these structures can guide information extraction, sentiment analysis, machine translation, question answering, essay scoring, text summarization, and thread recovery. 

Discourse segmentation can be defined as the process of determining the types of structures that will be used in large amounts of discourse. Implementing discourse segmentation is difficult, but it is critical for applications such as information retrieval, text summarization, and information extraction. Discourse Integration is dependent on the sentences that come before it and also invokes the meaning of the sentences that come after it. Unsupervised Discourse Segmentation and Supervised Discourse Segmentation are popularly used algorithms for discourse segmentation.